David Pond, Lead Product Manager, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
GraphSummit Milan - Visione e roadmap del prodotto Neo4jNeo4j
van Zoratti, VP of Product Management, Neo4j
Scoprite le ultime innovazioni di Neo4j che consentono un’intelligenza guidata dalle relazioni su scala. Scoprite le più recenti integrazioni nel cloud e i miglioramenti del prodotto che rendono Neo4j una scelta essenziale per gli sviluppatori che realizzano applicazioni con dati interconnessi e IA generativa.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
GraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptxNeo4j
The document discusses new features in Neo4j and a vision for integrating knowledge graphs with large language models. It summarizes recent Neo4j product updates including parallel query processing, change data capture, and auto-sharding. It then outlines how knowledge graphs can provide contextual connections and explainability to complement vector and LLM models. Examples of joint knowledge graph and LLM applications are described like conversational assistants, enhanced search, and generative AI. The document proposes that Neo4j can act as a grounding knowledge graph to power the next generation of generative AI applications through tight LLM integrations.
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4jNeo4j
Novedades de Productos y Roadmap Neo4j
Luis Salvador, Ingeniero de Preventas, Neo4j
Echa un vistazo a las últimas innovaciones de Neo4j que permiten la inteligencia basada en relaciones a escala. Obtenga más información sobre las últimas integraciones en la nube y mejoras de productos que hacen de Neo4j una opción esencial para los desarrolladores que crean aplicaciones con datos interconectados e IA generativa.
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4jNeo4j
Novedades de Productos y Roadmap Neo4j
Luis Salvador, Ingeniero de Preventas, Neo4j
Echa un vistazo a las últimas innovaciones de Neo4j que permiten la inteligencia basada en relaciones a escala. Obtenga más información sobre las últimas integraciones en la nube y mejoras de productos que hacen de Neo4j una opción esencial para los desarrolladores que crean aplicaciones con datos interconectados e IA generativa.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
The Path To Success With Graph Database and AnalyticsNeo4j
This document discusses Neo4j's graph database and analytics platform. It provides an overview of the platform's capabilities including graph data science, machine learning, algorithms, and ecosystem integrations. It also presents examples of how the platform has been used for applications like fraud detection and recommendations. New features are highlighted such as improved algorithms, machine learning pipelines, and GNN support. Overall, the document promotes Neo4j's graph database as an integrated platform for knowledge graphs, analytics, and machine learning on connected data.
GraphSummit Milan - Visione e roadmap del prodotto Neo4jNeo4j
van Zoratti, VP of Product Management, Neo4j
Scoprite le ultime innovazioni di Neo4j che consentono un’intelligenza guidata dalle relazioni su scala. Scoprite le più recenti integrazioni nel cloud e i miglioramenti del prodotto che rendono Neo4j una scelta essenziale per gli sviluppatori che realizzano applicazioni con dati interconnessi e IA generativa.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
GraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptxNeo4j
The document discusses new features in Neo4j and a vision for integrating knowledge graphs with large language models. It summarizes recent Neo4j product updates including parallel query processing, change data capture, and auto-sharding. It then outlines how knowledge graphs can provide contextual connections and explainability to complement vector and LLM models. Examples of joint knowledge graph and LLM applications are described like conversational assistants, enhanced search, and generative AI. The document proposes that Neo4j can act as a grounding knowledge graph to power the next generation of generative AI applications through tight LLM integrations.
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4jNeo4j
Novedades de Productos y Roadmap Neo4j
Luis Salvador, Ingeniero de Preventas, Neo4j
Echa un vistazo a las últimas innovaciones de Neo4j que permiten la inteligencia basada en relaciones a escala. Obtenga más información sobre las últimas integraciones en la nube y mejoras de productos que hacen de Neo4j una opción esencial para los desarrolladores que crean aplicaciones con datos interconectados e IA generativa.
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4jNeo4j
Novedades de Productos y Roadmap Neo4j
Luis Salvador, Ingeniero de Preventas, Neo4j
Echa un vistazo a las últimas innovaciones de Neo4j que permiten la inteligencia basada en relaciones a escala. Obtenga más información sobre las últimas integraciones en la nube y mejoras de productos que hacen de Neo4j una opción esencial para los desarrolladores que crean aplicaciones con datos interconectados e IA generativa.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
The Path To Success With Graph Database and AnalyticsNeo4j
This document discusses Neo4j's graph database and analytics platform. It provides an overview of the platform's capabilities including graph data science, machine learning, algorithms, and ecosystem integrations. It also presents examples of how the platform has been used for applications like fraud detection and recommendations. New features are highlighted such as improved algorithms, machine learning pipelines, and GNN support. Overall, the document promotes Neo4j's graph database as an integrated platform for knowledge graphs, analytics, and machine learning on connected data.
Neo4j: The path to success with Graph Database and Graph Data ScienceNeo4j
This document provides an overview of the Neo4j graph data platform and its capabilities for data science and analytics. It discusses Neo4j's native graph architecture, tools for data scientists and analysts, and how Neo4j enables graph data science across the machine learning lifecycle from feature engineering to model deployment. Algorithms, embeddings, and machine learning pipelines in Neo4j are highlighted. Integration with common data ecosystems is also covered.
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdfNeo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
The path to success with graph database and graph data science_ Neo4j GraphSu...Neo4j
What’s new, and what’s next? Product innovation moves rapidly at Neo4j – learn how graph technology can provide you with the tools to get much more from your data!
The document outlines Neo4j's product strategy and roadmap. It discusses trends like increasing cloud adoption and the blending of transactional and analytical use cases. The roadmap focuses on cloud-first capabilities, ease of use for developers, trusted fundamentals of the database, and enabling AI through graph algorithms and knowledge graphs. Key announcements include new graph algorithms, change data capture for integration, autonomous clustering for scalability, and innovations in graph embeddings and generative AI integration.
Join this hands-on workshop led by Neo4j experts guiding you to systematically uncover contextual intelligence. Using a real-life dataset we will build step-by-step a graph solution; from building the graph data model to running queries and data visualization. The approach will be applicable across multiple use cases and industries.
Webinar - IA generativa e grafi Neo4j: RAG time!Neo4j
Here are the key limitations of using vector databases for RAG:
1. Schema-less - Vector databases don't enforce a schema, making it difficult to represent structured knowledge like entities, relationships and properties.
2. Indexing challenges - It's hard to efficiently index and retrieve data based on semantic relationships rather than just keywords.
3. Explainability - Without an explicit graph structure, it's difficult to explain how a particular piece of retrieved data is relevant or related to the user's question.
4. Knowledge representation - Vector spaces are not well-suited for representing hierarchical, multi-relational knowledge like you would find in a knowledge graph.
A graph database overcomes these limitations by providing an
This document provides an overview and roadmap of Neo4j product updates. It discusses the property graph model used by Neo4j and the Cypher query language. It summarizes new capabilities in Neo4j 5 such as graph schema, improved graph pattern matching, and parallel query processing. The document also mentions upcoming features like auto-sharding and integrations with Google Dataflow. Finally, it briefly introduces new graph algorithms for edge embeddings, longest path, and topological sorting.
This document provides an overview of Neo4j's vision and roadmap. It discusses Neo4j's goal of being a modern, enterprise data platform that can power both operational and analytical workloads. Key aspects of Neo4j's strategy include building a fully cloud-native database designed for operational and analytical graph workloads, with autonomous clustering to provide unlimited horizontal scalability. The document also briefly reviews recent Neo4j releases and highlights some new features like graph pattern matching and change data capture.
The path to success with Graph Database and Graph Data ScienceNeo4j
What’s new and what’s next? Product innovation moves rapidly at Neo4j – learn how graph technology can provide you with the tools to get much more from your data!
This document provides a roadmap for developing an enterprise graph strategy. It outlines key steps such as identifying a use case, designing a graph model using sample data, building APIs and demo applications, and deploying to production. It also provides examples of graph architectures, data processing techniques, and analytics capabilities. The goal is to solve a "graphy problem" by connecting disparate data sources and enabling new questions to be answered through graph queries and algorithms.
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
Cross-Tier Application and Data Partitioning of Web Applications for Hybrid C...nimak
This document discusses cross-tier application and data partitioning for hybrid cloud deployment. It motivates combining private and public clouds to split web application architectures. It proposes analyzing code and data dependencies, alternative execution plans, and using an integer programming model to determine optimal placements of code and data across tiers and clouds. An evaluation of two sample applications deployed in different configurations found that cross-tier partitioning improved performance by 28-56% and reduced costs by 20-54% compared to alternative approaches.
Your Roadmap for An Enterprise Graph StrategyNeo4j
This document provides a roadmap for developing an enterprise graph strategy with the following key steps:
1. Design and build a proof-of-concept graph using a small local dataset to demonstrate graph capabilities.
2. Present use cases and example queries to business stakeholders to validate the graph model and gather feedback.
3. Design the production graph schema and build APIs/services to integrate data from multiple sources.
4. Deploy the graph in the cloud and develop applications and reports to mobilize enterprise data using the graph.
Workshop 1. Architecting Innovative Graph Applications
Join this hands-on workshop for beginners led by Neo4j experts guiding you to systematically uncover contextual intelligence. Using a real-life dataset we will build step-by-step a graph solution; from building the graph data model to running queries and data visualization. The approach will be applicable across multiple use cases and industries.
This document discusses knowledge graphs and how they can transform businesses by providing dynamic context. It provides examples of how knowledge graphs are used by companies like Neo4j, Caterpillar, the US Army, and Boston Scientific. It outlines a methodology for creating a knowledge graph and discusses how knowledge graphs can be used for applications like recommendations, knowledge management, and machine teaching.
Neo4j Aura on AWS: The Customer Choice for Graph DatabasesNeo4j
Neo4j, the leading enterprise graph platform, is now globally available on Amazon Web Services (AWS) as a fully managed, always-on database service.
Neo4j Aura Enterprise on AWS empowers organizations to rapidly build mission-critical, intelligent cloud-based applications backed by the performance, scale, security, and reliability that only the most deployed and most trusted graph technology can provide.
Customers like Levi Strauss & Co., Sainsbury’s, Siemens, The Orchard and Tourism Media are already using Aura Enterprise on AWS for fraud detection, regulatory compliance, recommendation engines, supply chain analysis, and much more.
Join us for this exclusive digital event to learn more about Neo4j Aura Enterprise on AWS:
- Understand the state of the data and analytics market and how investing in Neo4j and AWS fits in the big picture
- Get insights into how Siemens and Tourism Media are unlocking the power of graph databases on AWS during a panel discussion
- Discover how to build modern graph applications with Neo4j on AWS through a step-by-step presentation and demo
Neo4j & AWS Bedrock workshop at GraphSummit London 14 Nov 2023.pptxNeo4j
The document provides information about a hands-on lab with Neo4j and Amazon Bedrock. It includes an introduction to Neo4j and graph databases. The lab instructions direct users to complete the first three labs on the Neo4j-partners GitHub repository, which involve loading data into Neo4j and querying the graph. The document also discusses how Neo4j can be used within the AWS ecosystem and partnerships between Neo4j and AWS.
Neo4j 5 introduces several new features and changes for administrators including:
1) Incremental offline data imports that are 10-100x faster than previous versions.
2) New index types that replace BTREE indexes and improve performance.
3) Autonomous clustering that automatically allocates databases across servers for high availability and scalability.
4) Composite databases that allow querying across multiple databases to scale beyond a single database.
Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24Neo4j
Join us for an exclusive workshop exploring the transformative benefits of Neo4j Aura, a cloud-native Database-as-a-Service (DBaaS). Neo4j Aura is revolutionizing data management and analysis, empowering organizations to unlock deeper insights, streamline operations, drive innovation, and return completeness of answers like never before.
Secure your spot for this comprehensive workshop as we dive into the revolutionary world of Neo4j's Aura that is transforming how organizations harness the potential of their interconnected data.
This workshop will:
Discuss the advantages and benefits of using a graph database-as-a-service, like the ease of deployment and enterprise-grade security and compliance measures
Highlight AuraDS - a managed service for running data science algorithms and workloads for Neo4j
Uncover the importance of grounding LLMs with knowledge graphs
Share integration and migration tips when transitioning or adding Aura Enterprise
Don't miss this opportunity to discover how Neo4j Aura can transform your approach to data relationships and unlock the true power of interconnected data!
Neo4j : la voie du succès avec les bases de données de graphes et la Graph Da...Neo4j
GraphSummit Paris
Nicolas Rouyer, Senior Presales Consultant, Neo4j
L’innovation produit évolue rapidement chez Neo4j – découvrez comment la technologie des graphes peut vous fournir les outils nécessaires pour obtenir beaucoup plus de vos données.
Neo4j: The path to success with Graph Database and Graph Data ScienceNeo4j
This document provides an overview of the Neo4j graph data platform and its capabilities for data science and analytics. It discusses Neo4j's native graph architecture, tools for data scientists and analysts, and how Neo4j enables graph data science across the machine learning lifecycle from feature engineering to model deployment. Algorithms, embeddings, and machine learning pipelines in Neo4j are highlighted. Integration with common data ecosystems is also covered.
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdfNeo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
The path to success with graph database and graph data science_ Neo4j GraphSu...Neo4j
What’s new, and what’s next? Product innovation moves rapidly at Neo4j – learn how graph technology can provide you with the tools to get much more from your data!
The document outlines Neo4j's product strategy and roadmap. It discusses trends like increasing cloud adoption and the blending of transactional and analytical use cases. The roadmap focuses on cloud-first capabilities, ease of use for developers, trusted fundamentals of the database, and enabling AI through graph algorithms and knowledge graphs. Key announcements include new graph algorithms, change data capture for integration, autonomous clustering for scalability, and innovations in graph embeddings and generative AI integration.
Join this hands-on workshop led by Neo4j experts guiding you to systematically uncover contextual intelligence. Using a real-life dataset we will build step-by-step a graph solution; from building the graph data model to running queries and data visualization. The approach will be applicable across multiple use cases and industries.
Webinar - IA generativa e grafi Neo4j: RAG time!Neo4j
Here are the key limitations of using vector databases for RAG:
1. Schema-less - Vector databases don't enforce a schema, making it difficult to represent structured knowledge like entities, relationships and properties.
2. Indexing challenges - It's hard to efficiently index and retrieve data based on semantic relationships rather than just keywords.
3. Explainability - Without an explicit graph structure, it's difficult to explain how a particular piece of retrieved data is relevant or related to the user's question.
4. Knowledge representation - Vector spaces are not well-suited for representing hierarchical, multi-relational knowledge like you would find in a knowledge graph.
A graph database overcomes these limitations by providing an
This document provides an overview and roadmap of Neo4j product updates. It discusses the property graph model used by Neo4j and the Cypher query language. It summarizes new capabilities in Neo4j 5 such as graph schema, improved graph pattern matching, and parallel query processing. The document also mentions upcoming features like auto-sharding and integrations with Google Dataflow. Finally, it briefly introduces new graph algorithms for edge embeddings, longest path, and topological sorting.
This document provides an overview of Neo4j's vision and roadmap. It discusses Neo4j's goal of being a modern, enterprise data platform that can power both operational and analytical workloads. Key aspects of Neo4j's strategy include building a fully cloud-native database designed for operational and analytical graph workloads, with autonomous clustering to provide unlimited horizontal scalability. The document also briefly reviews recent Neo4j releases and highlights some new features like graph pattern matching and change data capture.
The path to success with Graph Database and Graph Data ScienceNeo4j
What’s new and what’s next? Product innovation moves rapidly at Neo4j – learn how graph technology can provide you with the tools to get much more from your data!
This document provides a roadmap for developing an enterprise graph strategy. It outlines key steps such as identifying a use case, designing a graph model using sample data, building APIs and demo applications, and deploying to production. It also provides examples of graph architectures, data processing techniques, and analytics capabilities. The goal is to solve a "graphy problem" by connecting disparate data sources and enabling new questions to be answered through graph queries and algorithms.
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
Cross-Tier Application and Data Partitioning of Web Applications for Hybrid C...nimak
This document discusses cross-tier application and data partitioning for hybrid cloud deployment. It motivates combining private and public clouds to split web application architectures. It proposes analyzing code and data dependencies, alternative execution plans, and using an integer programming model to determine optimal placements of code and data across tiers and clouds. An evaluation of two sample applications deployed in different configurations found that cross-tier partitioning improved performance by 28-56% and reduced costs by 20-54% compared to alternative approaches.
Your Roadmap for An Enterprise Graph StrategyNeo4j
This document provides a roadmap for developing an enterprise graph strategy with the following key steps:
1. Design and build a proof-of-concept graph using a small local dataset to demonstrate graph capabilities.
2. Present use cases and example queries to business stakeholders to validate the graph model and gather feedback.
3. Design the production graph schema and build APIs/services to integrate data from multiple sources.
4. Deploy the graph in the cloud and develop applications and reports to mobilize enterprise data using the graph.
Workshop 1. Architecting Innovative Graph Applications
Join this hands-on workshop for beginners led by Neo4j experts guiding you to systematically uncover contextual intelligence. Using a real-life dataset we will build step-by-step a graph solution; from building the graph data model to running queries and data visualization. The approach will be applicable across multiple use cases and industries.
This document discusses knowledge graphs and how they can transform businesses by providing dynamic context. It provides examples of how knowledge graphs are used by companies like Neo4j, Caterpillar, the US Army, and Boston Scientific. It outlines a methodology for creating a knowledge graph and discusses how knowledge graphs can be used for applications like recommendations, knowledge management, and machine teaching.
Neo4j Aura on AWS: The Customer Choice for Graph DatabasesNeo4j
Neo4j, the leading enterprise graph platform, is now globally available on Amazon Web Services (AWS) as a fully managed, always-on database service.
Neo4j Aura Enterprise on AWS empowers organizations to rapidly build mission-critical, intelligent cloud-based applications backed by the performance, scale, security, and reliability that only the most deployed and most trusted graph technology can provide.
Customers like Levi Strauss & Co., Sainsbury’s, Siemens, The Orchard and Tourism Media are already using Aura Enterprise on AWS for fraud detection, regulatory compliance, recommendation engines, supply chain analysis, and much more.
Join us for this exclusive digital event to learn more about Neo4j Aura Enterprise on AWS:
- Understand the state of the data and analytics market and how investing in Neo4j and AWS fits in the big picture
- Get insights into how Siemens and Tourism Media are unlocking the power of graph databases on AWS during a panel discussion
- Discover how to build modern graph applications with Neo4j on AWS through a step-by-step presentation and demo
Neo4j & AWS Bedrock workshop at GraphSummit London 14 Nov 2023.pptxNeo4j
The document provides information about a hands-on lab with Neo4j and Amazon Bedrock. It includes an introduction to Neo4j and graph databases. The lab instructions direct users to complete the first three labs on the Neo4j-partners GitHub repository, which involve loading data into Neo4j and querying the graph. The document also discusses how Neo4j can be used within the AWS ecosystem and partnerships between Neo4j and AWS.
Neo4j 5 introduces several new features and changes for administrators including:
1) Incremental offline data imports that are 10-100x faster than previous versions.
2) New index types that replace BTREE indexes and improve performance.
3) Autonomous clustering that automatically allocates databases across servers for high availability and scalability.
4) Composite databases that allow querying across multiple databases to scale beyond a single database.
Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24Neo4j
Join us for an exclusive workshop exploring the transformative benefits of Neo4j Aura, a cloud-native Database-as-a-Service (DBaaS). Neo4j Aura is revolutionizing data management and analysis, empowering organizations to unlock deeper insights, streamline operations, drive innovation, and return completeness of answers like never before.
Secure your spot for this comprehensive workshop as we dive into the revolutionary world of Neo4j's Aura that is transforming how organizations harness the potential of their interconnected data.
This workshop will:
Discuss the advantages and benefits of using a graph database-as-a-service, like the ease of deployment and enterprise-grade security and compliance measures
Highlight AuraDS - a managed service for running data science algorithms and workloads for Neo4j
Uncover the importance of grounding LLMs with knowledge graphs
Share integration and migration tips when transitioning or adding Aura Enterprise
Don't miss this opportunity to discover how Neo4j Aura can transform your approach to data relationships and unlock the true power of interconnected data!
Neo4j : la voie du succès avec les bases de données de graphes et la Graph Da...Neo4j
GraphSummit Paris
Nicolas Rouyer, Senior Presales Consultant, Neo4j
L’innovation produit évolue rapidement chez Neo4j – découvrez comment la technologie des graphes peut vous fournir les outils nécessaires pour obtenir beaucoup plus de vos données.
Similar to GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product Updates (20)
Atelier - Architecture d’applications de Graphes - GraphSummit ParisNeo4j
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Participez à cet atelier pratique animé par des experts de Neo4j qui vous guideront pour découvrir l’intelligence contextuelle. En utilisant un jeu de données réel, nous construirons étape par étape une solution de graphes ; de la construction du modèle de données de graphes à l’exécution de requêtes et à la visualisation des données. L’approche sera applicable à de multiples cas d’usages et industries.
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La Génération de Récupération Augmentée (RAG) permet la réponse à des questions d’utilisateur sur un domaine métier à l’aide de grands modèles de langage. Cette technique fonctionne correctement lorsque la documentation est simple mais trouve des limitations dès que les sources sont complexes. Au travers d’un projet que nous avons réalisé, nous vous présenterons l’approche GraphRAG, une nouvelle approche qui utilise une base Neo4j générée pour améliorer la compréhension des documents et la synthèse d’informations. Cette méthode surpasse l’approche RAG en fournissant des réponses plus holistiques et précises.
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Charles Gouwy, Business Product Leader, Adeo Services (Groupe Leroy Merlin)
Alors que leur Knowledge Graph est déjà intégré sur l’ensemble des expériences d’achat de leur plateforme e-commerce depuis plus de 3 ans, nous verrons quelles sont les nouvelles opportunités et challenges qui s’ouvrent encore à eux grâce à leur utilisation d’une base de donnée de graphes et l’émergence de l’IA.
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Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
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Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
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Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
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Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
GraphAware - Transforming policing with graph-based intelligence analysisNeo4j
Petr Matuska, Sales & Sales Engineering Lead, GraphAware
Western Australia Police Force’s adoption of Neo4j and the GraphAware Hume graph analytics platform marks a significant advancement in data-driven policing. Facing the challenges of growing volumes of valuable data scattered in disconnected silos, the organisation successfully implemented Neo4j database and Hume, consolidating data from various sources into a dynamic knowledge graph. The result was a connected view of intelligence, making it easier for analysts to solve crime faster. The partnership between Neo4j and GraphAware in this project demonstrates the transformative impact of graph technology on law enforcement’s ability to leverage growing volumes of valuable data to prevent crime and protect communities.
Shirley Bacso, Data Architect, Ingka Digital
“Linked Metadata by Design” represents the integration of the outcomes from human collaboration, starting from the design phase of data product development. This knowledge is captured in the Data Knowledge Graph. It not only enables data products to be robust and compliant but also well-understood and effectively utilized.
Your enemies use GenAI too - staying ahead of fraud with Neo4jNeo4j
Delivered by Michael Down at Gartner Data & Analytics Summit London 2024 - Your enemies use GenAI too: Staying ahead of fraud with Neo4j.
Fraudsters exploit the latest technologies like generative AI to stay undetected. Static applications can’t adapt quickly enough. Learn why you should build flexible fraud detection apps on Neo4j’s native graph database combined with advanced data science algorithms. Uncover complex fraud patterns in real-time and shut down schemes before they cause damage.
BT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptxNeo4j
Delivered by Sreenath Gopalakrishna, Director of Software Engineering at BT, and Dr Jim Webber, Chief Scientist at Neo4j, at Gartner Data & Analytics Summit London 2024 this presentation examines how knowledge graphs and GenAI combine in real-world solutions.
BT Group has used the Neo4j Graph Database to enable impressive digital transformation programs over the last 6 years. By re-imagining their operational support systems to adopt self-serve and data lead principles they have substantially reduced the number of applications and complexity of their operations. The result has been a substantial reduction in risk and costs while improving time to value, innovation, and process automation. Future innovation plans include the exploration of uses of EKG + Generative AI.
Workshop: Enabling GenAI Breakthroughs with Knowledge Graphs - GraphSummit MilanNeo4j
Look beyond the hype and unlock practical techniques to responsibly activate intelligence across your organization’s data with GenAI. Explore how to use knowledge graphs to increase accuracy, transparency, and explainability within generative AI systems. You’ll depart with hands-on experience combining relationships and LLMs for increased domain-specific context and enhanced reasoning.
LARUS - Galileo.XAI e Gen-AI: la nuova prospettiva di LARUS per il futuro del...Neo4j
Roberto Sannino, Larus Business Automation
Nel panorama sempre più complesso dei progetti basati su grafi, LARUS ha consolidato una solida esperienza pluriennale, costruendo un rapporto di fiducia e collaborazione con Neo4j. Attraverso il LARUS Labs, ha sviluppato componenti e connettori che arricchiscono l’ecosistema Neo4j, contribuendo alla sua continua evoluzione. Tutto questo know-how è stato incanalato nell’innovativa soluzione Galileo.XAI di LARUS, un prodotto all’avanguardia che, integrato con la Generative AI, offre una nuova prospettiva nel mondo dell’Intelligenza Artificiale Spiegabile applicata ai grafi. In questo speech, si esplorerà il percorso di crescita di LARUS in questo settore, mettendo in luce le potenzialità della soluzione Galileo.XAI nel guidare l’innovazione e la trasformazione digitale.
LIVE DEMO: CCX for CSPs, a drop-in DBaaS solutionSeveralnines
This webinar aims to equip Cloud Service Providers (CSPs) with the knowledge and tools to differentiate themselves from hyperscalers by offering a Database-as-a-Service (DBaaS) solution. The session will introduce and demonstrate CCX, a drop-in, premium DBaaS designed for rapid adoption.
Learn more about CCX for CSPs here: https://bit.ly/3VabiDr
Tired of managing scheduled tasks in the CFML engine administrators? Why does everything have to be a URL? How can I test my tasks? How can I make them portable? How can I make them more human, for Pete’s sake? Now you can with Box Tasks!
Join me for an insightful journey into task scheduling within the ColdBox framework for ANY CFML application, not only ColdBox. In this session, we’ll dive into how you can effortlessly create and manage scheduled tasks directly in your code, bringing a new level of control and efficiency to your applications and modules. You’ll also get a first-hand look at a user-friendly dashboard that makes managing and monitoring these tasks a breeze. Whether you’re a ColdBox veteran or just starting, this session will offer practical knowledge and tips to enhance your development workflow. Let’s explore how task scheduling in ColdBox can simplify your development process and elevate your applications.
Strengthening Web Development with CommandBox 6: Seamless Transition and Scal...Ortus Solutions, Corp
Join us for a session exploring CommandBox 6’s smooth website transition and efficient deployment. CommandBox revolutionizes web development, simplifying tasks across Linux, Windows, and Mac platforms. Gain insights and practical tips to enhance your development workflow.
Come join us for an enlightening session where we delve into the smooth transition of current websites and the efficient deployment of new ones using CommandBox 6. CommandBox has revolutionized web development, consistently introducing user-friendly enhancements that catalyze progress in the field. During this presentation, we’ll explore CommandBox’s rich history and showcase its unmatched capabilities within the realm of ColdFusion, covering both major variations.
The journey of CommandBox has been one of continuous innovation, constantly pushing boundaries to simplify and optimize development processes. Regardless of whether you’re working on Linux, Windows, or Mac platforms, CommandBox empowers developers to streamline tasks with unparalleled ease.
In our session, we’ll illustrate the simple process of transitioning existing websites to CommandBox 6, highlighting its intuitive features and seamless integration. Moreover, we’ll unveil the potential for effortlessly deploying multiple websites, demonstrating CommandBox’s versatility and adaptability.
Join us on this journey through the evolution of web development, guided by the transformative power of CommandBox 6. Gain invaluable insights, practical tips, and firsthand experiences that will enhance your development workflow and embolden your projects.
In recent years, technological advancements have reshaped human interactions and work environments. However, with rapid adoption comes new challenges and uncertainties. As we face economic challenges in 2023, business leaders seek solutions to address their pressing issues.
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Streamlining End-to-End Testing Automation with Azure DevOps Build & Release Pipelines
Automating end-to-end (e2e) test for Android and iOS native apps, and web apps, within Azure build and release pipelines, poses several challenges. This session dives into the key challenges and the repeatable solutions implemented across multiple teams at a leading Indian telecom disruptor, renowned for its affordable 4G/5G services, digital platforms, and broadband connectivity.
Challenge #1. Ensuring Test Environment Consistency: Establishing a standardized test execution environment across hundreds of Azure DevOps agents is crucial for achieving dependable testing results. This uniformity must seamlessly span from Build pipelines to various stages of the Release pipeline.
Challenge #2. Coordinated Test Execution Across Environments: Executing distinct subsets of tests using the same automation framework across diverse environments, such as the build pipeline and specific stages of the Release Pipeline, demands flexible and cohesive approaches.
Challenge #3. Testing on Linux-based Azure DevOps Agents: Conducting tests, particularly for web and native apps, on Azure DevOps Linux agents lacking browser or device connectivity presents specific challenges in attaining thorough testing coverage.
This session delves into how these challenges were addressed through:
1. Automate the setup of essential dependencies to ensure a consistent testing environment.
2. Create standardized templates for executing API tests, API workflow tests, and end-to-end tests in the Build pipeline, streamlining the testing process.
3. Implement task groups in Release pipeline stages to facilitate the execution of tests, ensuring consistency and efficiency across deployment phases.
4. Deploy browsers within Docker containers for web application testing, enhancing portability and scalability of testing environments.
5. Leverage diverse device farms dedicated to Android, iOS, and browser testing to cover a wide range of platforms and devices.
6. Integrate AI technology, such as Applitools Visual AI and Ultrafast Grid, to automate test execution and validation, improving accuracy and efficiency.
7. Utilize AI/ML-powered central test automation reporting server through platforms like reportportal.io, providing consolidated and real-time insights into test performance and issues.
These solutions not only facilitate comprehensive testing across platforms but also promote the principles of shift-left testing, enabling early feedback, implementing quality gates, and ensuring repeatability. By adopting these techniques, teams can effectively automate and execute tests, accelerating software delivery while upholding high-quality standards across Android, iOS, and web applications.
About 10 years after the original proposal, EventStorming is now a mature tool with a variety of formats and purposes.
While the question "can it work remotely?" is still in the air, the answer may not be that obvious.
This talk can be a mature entry point to EventStorming, in the post-pandemic years.
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GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product Updates
1. Neo4j Inc. All rights reserved 2024
Neo4j Product Vision
and Roadmap
David Pond
Lead Product Manager
2. Neo4j Inc. All rights reserved 2024
SAFE HARBOR ROADMAP
DISCLAIMER
The information presented here is Neo4j, Inc. confidential and does not
constitute, and should not be construed as, a promise or commitment by
Neo4j to develop, market or deliver any particular product, feature or
function.
Neo4j reserves the right to change its product plans or roadmap at any
time, without obligation to notify any person of such changes.
The timing and content of Neo4j’s future product releases could differ
materially from the expectations discussed herein.
2
4. Neo4j
Product capabilities launched in 2023/2024
Neo4j Inc. All rights reserved 2024
5
● Parallel Runtime - faster analytical Queries
● Change Data Capture - better data integration
● Autonomous clustering & Fabric - limitless
scalability
● Graph Schema & constraints
● Backup with point-in-time recovery
● Incremental import
● Neo4j/AuraDB Ops Manager for managing
databases
● Aura Enterprise Database on all clouds
(AWS, GCP, Azure)
● SOC II Type 2 compliance, AuraDB APIs, RBAC
configuration
● Private Link & CMEK
● Log forwarding & performance metrics - better
observability
● Workspace - unified developer experience
● GraphQL Support & Simplified Drivers API
● Bloom support for GDS algorithms
● GDS Python API
● Knowledge Graph Embeddings
● Longest Path & Topological Sort Algorithm
● Vector Search & index
● Embedding APIs & LLM Models - Real Time
integration
● OpenAI + MS Azure OpenAI, VertexAI, AWS
Bedrock, Langchain, LlamaIndex etc. - Real Time
GenAI integration
5. Neo4j Inc. All rights reserved 2024
6
Cloud Scale
• Procure through Aura Console or via
Cloud Marketplace
• Zero maintenance, automated
upgrades and highly available
• Scalable and elastic, on-demand
• Enterprise-grade security
• SOC II Type 2 compliance
• Easier RBAC configuration with Aura
Console
• Private link
• CMEK
• Observability with Ops Manager,
performance metrics and logs
forwarding
6. Customer Managed Keys (Encryption)
7 Neo4j Inc. All rights reserved 2024
What is it
Aura encrypts all data at transit &
rest by default.
Customer Managed Keys (CMK)
is an alternative way to protect
cloud data for security conscious
Enterprises, enabling customers
to manage their own keys for
encryption / decryption at disk on
Aura using Key Management
Services (KMS) from their Cloud
Service Provider.
Why it is important
Customers can protect their own
data, control access and have
the ability to revoke access, even
from Neo4j.
Customers can adhere to their
own stringent security policy
around access and key rotation,
on top of Aura’s Enterprise grade
default security and compliance
posture.
10. Improvements in Bloom / Explore
Neo4j Inc. All rights reserved 2024
Neo4j Inc. All rights reserved 2024
Data Slicer
GDS Algos
11. Neo4j Inc. All rights reserved 2024
12
April 12, 2024
Welcome GQL!
GQL - Graph Query Language
The first new ISO language since 1987
GQL-fueled additions in Cypher:
• Node and relationship expressions WHERE
clause
• Richer label expressions
• Sophisticated pattern repetitions
• SQL-like synonims
• GQL Error codes
• GQL is Here: Your Cypher Queries in a GQL World
• GQL: The ISO Standard for Graphs Has Arrived
• ISO GQL: A Defining Moment in the History of
Database Innovation
12. Neo4j Inc. All rights reserved 2024
13
Graph Pattern
Matching
Improved expressivity of
graph navigation with
Quantified Path Patterns,
a more powerful and
performant syntax to
navigate and traverse
your graph.
13. NEO4J 5.0 NEW CAPABILITIES
Database Enhancements
Graph Pattern Matching Example → Fraud Rings
Neo4j Inc. All rights reserved 2024
14
QPP
MATCH path=(a:Account)-[:PERFORMS]->(first_tx)
((tx_i)-[:BENEFITS_TO]->(a_i)-[:PERFORMS]->(tx_j)
WHERE tx_i.date < tx_j.date
AND 0.80 <= tx_i.amount / tx_j.amount <= 1.00
){3,6}
(last_tx)-[:BENEFITS_TO]->(a)
WHERE size(apoc.coll.toSet([a]+a_i)) = size([a]+a_i)
RETURN path
accountNumber:2
amount: 1000
date: 2023-01-01T10:10:10.000+0000
accountNumber: 1
amount: 900
date: 2023-01-02T10:10:10.000+0000
amount: 729
date: 2023-01-04T10:10:10.000+0000
accountNumber: 4
accountNumber: 3
14. Neo4j Inc. All rights reserved 2024
15
New constraints on nodes,
relationships and properties:
● Node/Relationship unique
property
● Node/Relationship property
existence and type
● Node/Relationship keys
NEO4J 5 NEW CAPABILITIES
Graph Schema
15. Graph Schema / Graph Type
Neo4j Inc. All rights reserved 2024
16
The definition of the informational content of a schema
(or rather a graph type), comprising:
● A set of node type descriptors
(also known as a node type set).
● A set of edge type descriptors
(also known as an edge type set).
● A node type name dictionary that maps node type
names,
which are identifiers, to node types contained in the node
type set of this graph type descriptor such that each
node type name is mapped to a single node type.
● An edge type name dictionary that maps edge
type names,
which are identifiers, to edge types contained in the
edge type set of this graph type descriptor such that
each edge type name is mapped to a single edge type.
CREATE OR REPLACE GRAPH TYPE FraudDet
(a:AccountHolder { FirstName :: STRING!,
LastName :: STRING!,
UniqueId :: STRING! }
...) REQUIRE UniqueId IS KEY,
(c:CreditCard {AccountNumber :: STRING!,
Balance :: FLOAT!,
...} ...) REQUIRE AccountNumber IS KEY, ...
(a)-[:HAS_CARD ...]->(c),
(a)-[:HAS_ACCOUNT ...]->(b),...
CREATE OR REPLACE DATABASE foo
...
[WITH GRAPH TYPE FrautDet]
...
16. Neo4j Inc. All rights reserved 2024
17
Parallel Runtime
Speed up
analytical
queries up to
100x
17. Neo4j Inc. All rights reserved 2024
18
Parallel Runtime
Speed up
analytical
queries up to
100x
18. Neo4j Inc. All rights reserved 2024
19
Parallel Runtime
Speed up
analytical
queries up to
100x MORE CORES
19. Neo4j Inc. All rights reserved 2024
20
Parallel Runtime
Speed up
analytical
queries up to
100x
FASTER
QUERIES
MORE CORES
20. Neo4j Inc. All rights reserved 2024
21
BLOCK FORMAT
Memory Optimized
and Future Proof
An implementation of graph-native
that’s informed by more than a decade
of experience supporting real-world
production graph workloads.
Neo4j is still graph-first; block format
is:
• Native graph storage
• Optimized for connected data
• Index-free adjacency
Block format supersedes all previous
store formats.
Migrate, convert, import into Block
Format
22. Graph Data at Scale
23 Neo4j Inc. All rights reserved 2024
Autonomous Clustering
Easy, automated horizontal scale-
out
Composite Databases
Federated queries and sharded graphs
23. Graph Data at Scale
24 Neo4j Inc. All rights reserved 2024
24. Properties Sharding
25 Neo4j Inc. All rights reserved 2024
Users’ Connections TOPOLOGY DATABASE
SHARDED PROPERTY
DATABASES
Parallel
data load
Rolling
updates on
demand
25. AI Enabler
Graph Data Science & Generative AI
Neo4j Inc. All rights reserved 2024
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27. Neo4j Inc. All rights reserved 2023
Neo4j Inc. All rights reserved 2024
28
Knowledge Graphs + LLMs
28
Facts
Explicit
Explainable
Words
Implicit
Opaque
KGs LLMs
+
Left Brain + Right Brain
28. Retrieval Augmented Generation (GraphRAG)
Vector + Graph Search
Neo4j Inc. All rights reserved 2024
29
● avoid hallucinations
● ignore LLM training data
● only use language skills
● fetch relevant information from
reliable (enterprise) datasources
● often uses vector and/or full-text
search for starting points
● use context from knowledge graph
29. Graph + Vector = Semantic Search
Neo4j Inc. All rights reserved 2024
30
Find similar documents.
Find related information.
Combine for more
accurate results within a
relevant context.
Vector Index
Graph Structure
Knowledge Graph
Similarity Search
Pattern Matching
30. 31
What is a Knowledge Graph?
An information architecture with layered connections.
Or a digital twin of reality or your organization.
Neo4j Inc. All rights reserved 2024
DATA INFORMATION KNOWLEDGE INSIGHT MEANING
records sets relationships patterns layers
31. RAG with Neo4j
Neo4j Inc. All rights reserved 2024
32
Find similar documents,
content and data
Expanded context for related
information and ranking
results
Improve GenAI inferences and
insights. Discover new
relationships and entities
Unified search, knowledge graph and data science capabilities to
improve RAG quality and effectiveness
Vector Search,
Full-text Search,
Geospatial, Pattern
match
Data Science
Knowledge Graph
32. Neo4j Inc. All rights reserved 2023
Neo4j Inc. All rights reserved 2024
33
Knowledge Graph Complementary Benefits
33
LLM
Human
Application
Knowledge
Graph
Extend LLM
knowledge
through RAG
Invite human
exploration &
curation
Advanced
application
features & analysis
33. Neo4j Inc. All rights reserved 2024
34
1 Knowledge Graph Construction
Gen AI use cases LLM
Knowledge
Graph
neo4j.com/labs/genai-ecosystem/llm-graph-builder
34. Neo4j Inc. All rights reserved 2024
35
Knowledge Graph
Construction with
Cypher Templates
35. Neo4j Inc. All rights reserved 2024
36
Knowledge Graph Construction
neo4j.com/labs/genai-ecosystem/llm-graph-builder
36. Neo4j Inc. All rights reserved 2024
Human
37
1 Knowledge Graph Construction
Gen AI use cases LLM
Knowledge
Graph
2 RAG-based Chat Applications
neo4j.com/labs/genai-ecosystem/rag-demo/
37. Neo4j Inc. All rights reserved 2024
38
Natural Language
Search combining
explicit and implicit
relationships
38. Neo4j Inc. All rights reserved 2024
39
RAG-based Chat Applications
neo4j.com/labs/genai-ecosystem/rag-demo/
39. Neo4j Inc. All rights reserved 2024
Application Human
40
1 Knowledge Graph Construction
Gen AI use cases LLM
Knowledge
Graph
2 RAG-based Chat Applications
3 RAG-enhanced General Applications
40. Neo4j Inc. All rights reserved 2024
41
Natural Language
assistants and co-
pilots,
rooted in business
policy
Prompt +
Relevant
Information
Embedding API LLM API
User
Database
Search
Prompt Response
Relevant Results
Knowledge
Graph
Application
41. ● Integrate Neo4j with leading LLM open-
source frameworks such as LangChain,
LlamaIndex & More
● Call LLM APIs natively via Cypher using
product integration or open-source APOC
(extended) library
● Agnostic LLM orchestration connecting
graphs to OpenAI, AWS Bedrock, GCP
Vertex AI, Azure, Anthropic, Hugging
Face, and other proprietary and open
source foundation models
Integrate with the GenAI Ecosystem
Neo4j Inc. All rights reserved 2024
42
GenAI Stack
Application
Generative AI & Embedding Models
Orchestration
Grounding Knowledge Graph
Neo4jGraph
Neo4jVector
GraphCypherQAChai
n
Neo4jGraphStore
Neo4jVectorStore
KnowledgeGraphIndex
Neo4j GenAI Integrations
Text | Chat | Embedding
NL Query | Image Gen
Neo4j Drivers
Java
Python JavaScript
neo4j.com/labs/genai-ecosystem
42. POWERING GENERATIVE AI APPS
Neo4j’s GenAI Roadmap
● Co-Pilots & integrations in Neo4j Browser, Bloom,
Data Importer, NeoDash, Docs
● Cloud Integrations: GCP Vertex AI, AWS Bedrock,
Azure OpenAI
● Scalable and integrated Vector Search, additional
Graph Embeddings
● GraphRAG eval framework
● More framework integrations: Langchain,
LlamaIndex, SemanticKernel, Spring.AI, Haystack
Neo4j Inc. All rights reserved 2024
43
Coming 2024+
43. ● Parallel Runtime for faster analytical Queries
● Block Format for efficient and future proof graph
storage
● Change Data Capture (CDC) better data integration
● Autonomous clustering and Composite Database for
limitless scalability
● Graph Schema, Improved Backup recovery,
incremental import
● Neo4j Ops Manager for managing databases
● Aura Database on all clouds (AWS, GCP, Azure)
● SOC II Type 2 & HIPAA compliance, AuraDB APIs,
RBAC configuration
● Better observability with security log forwarding
Performance metrics forwarding (EAP)
● Private Link & CMEK
Neo4j product capabilities launched in 2023/24
Neo4j Inc. All rights reserved 2024
44
● Unified Developer Experience with Neo4j Workspace
● Quantified Graph Pattern Matching
● Call in Transactions
● Self-service Data Import (more coming soon)
● GraphQL Support
● Simplified Drivers API
● Bloom support for Graph Data Science algorithms
● Graph Data Science Client
● Knowledge Graph Embeddings
● Vector Index, similarity search & vector similarity
● Real Time integration with Embedding APIs & LLM
Models
● GenAI Integrations (OpenAI + MS Azure OpenAI,
VertexAI, AWS Bedrock, Langchain(Python & JS),
LlamaIndex, Haystack, Spring AI, LangChain4j)
44. Neo4j Inc. All rights reserved 2024
45
Follow us!
@neo4j
Enjoy
GraphSummit
Stockholm
david.pond@neo4j.com