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MongoDB to ScyllaDB: Technical Comparison and the Path to Success

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ScyllaDB
ScyllaDB

What can you expect when migrating from MongoDB to ScyllaDB? This session provides a jumpstart based on what we’ve learned from working with your peers across hundreds of use cases. Discover how ScyllaDB’s architecture, capabilities, and performance compares to MongoDB’s. Then, hear about your MongoDB to ScyllaDB migration options and practical strategies for success, including our top do’s and don’ts.

Technology
1 of 31
MongoDB vs ScyllaDB: Path to Success Felipe Mendes, Solution Architect at ScyllaDB Pete Aven, Solution Architect at ScyllaDB
Meet The Team Felipe Cardeneti Mendes ■ Published Author ■ ScyllaDB Committer ■ IT Specialist & Solution Architect Your photo goes here, smile :) Pete Aven ■ Data Engineer ■ Application Development ■ ScyllaDB Solution Architect
Soccer Football Goal?
Survival Rule #1
Lower Node Count Efficient hardware usage results in direct savings Where Do You Wanna Be? Predictable, Low Latencies Consistent single-digit millisecond p99 latencies Autonomous Self-Tuning Self-optimizing, smaller footprint, easy to use Always-On Architecture Active-active deployments for mission-critical workloads
Architecture Differences
Data Model & Query Language ■ MQL – Mongo Query Language ■ Documents stored in BSON format ■ Schemaless ■ Favors Query Flexibility over Performance
Data Model & Query Language ■ CQL or DynamoDB API ■ Wide-Column Representation ■ Schema-oriented ■ Favors Performance over Query Flexibility
MongoDB – Replica Sets Reads Reads (optional) Reads (optional) REPLICA SET 3x replication ■ Primary-Secondary ■ Impact on Write Throughput ■ Election on Failure ■ Scaling Limitations ■ Up to 50 members ■ Arbiters ■ Non-voting members ■ Limited Storage/Replica* ■ Affect Reads Scaling MongoDB Atlas *
MongoDB – Sharded Cluster ■ A Shard is a Replica Set ■ Adds Overhead & Complexity ■ Further Availability Concerns ■ Underutilized Capacity ■ Sharding ■ Performed Manually ■ Hashed vs Ranged ■ Still Require a Query Router Reads SHARDED CLUSTER 3 shards, 3x replication
ScyllaDB – Sharding & Replication ■ Simplified Architecture ■ Equal Nodes ■ Sharded to the Core ■ Maximizes Infrastructure Power ■ Unlimited Scale ■ Always-On ■ No Limits ■ Fully Autonomous App App
Independent Benchmark Results "ScyllaDB outperforms MongoDB in 132 of 133 measurements." – Daniel Seybold, benchANT CTO Read the full report
"MongoDB is Web Scale" "The scalability results demonstrate that ScyllaDB achieves up to near linear scalability, while MongoDB shows less efficient horizontal scalability." – Daniel Seybold, benchANT CTO Read the full report
Migration Options
It’s a Simple Matter of Programming(™)
Connectors Connecting ScyllaDB Shard-Aware Drivers
Collections vs Tables
Mental Exercise MemeGroup [ { id: simpsons, title: 'The Simpsons', author: uid1, tags: ['homer', 'liza'], photos: [pid1, pid2], views: 200 } { id: comics, title: 'Comics', author: uid2, tags: ['drawing', 'cartoon'], photos: [pid1, pid2, pid3], views: 300 } { id: matrix, title: 'Matrix', author: uid1, tags: ['neo', 'morpheus', 'pill'], photos: [pid4, pid5], views: 50 } ] Memes [ { id: homer_grass, title: 'Homer Hiding', location: p1, tags: ['hiding', 'grass'], likes: 30, views: 200 } { id: morpheus_pill, title: Choose Destiny', location: p2, tags: ['pills'], likes: 99, views: 300 } { id: trollface, title: 'Troll face', location: p3, tags: ['troll', 'face], likes: 9999999, views: NaN } ] ■ Queries: ■ Display all Memes posted by a given Author, sorted by time ■ Retrieve all Groups of Memes matching a particular Tag
Mental Exercise ■ Queries: ■ Display all Memes posted by a given Author, sorted by time ■ Retrieve all Groups of Memes matching a particular Tag CREATE TABLE MemeByAuthor ( author uuid, meme_id uuid, post_time timeuuid, title text, tags frozen<set<text>>, path text, PRIMARY KEY(author, post_time) ) CREATE TABLE MemeGroup ( group_id uuid, author_id uuid, title text, tags set<text>, memes uuid, PRIMARY KEY(group_id, memes) ) CREATE INDEX ON MemeGroup(tags); Adapted from StackOverflow
ScyllaDB JSON Support INSERT INTO mytable JSON '{ ""_id"": 1, "title": "Reservoir Dogs", "director": ...}' SELECT and INSERT statements
Leave JSON “As-Is” ID #1 document
Hybrid Approach ID #1 Document Document ID #1
Before Migrating ■ Understand the differences between a document vs wide-column ■ Denormalize and design a query-driven approach ■ Optimize your model for fast retrieval & ingestion ■ Take the opportunity to re-evaluate your access patterns! ■ Get to know the available data-types, indexes, collections and UDTs in ScyllaDB ■ Implement highly concurrent asynchronous code in your application ■ BLAST ScyllaDB – It WILL handle it!
Migration Walkthrough ETL Application Writes & Reads Reads Forklift Historical Data Source Connector MongoDB Change Streams ScyllaDB Sink Connector Writes & Reads
Success Stories
Trillions of messages 60% fewer nodes 5msp99 "We knew we were not going to use MongoDB sharding because it is complicated to use and not known for stability" 2015 – Million 2016 – Billion 2019 – Trillion Stanislav Vishnevskiy How Discord Stores Billions and Trillions of
Unleashing the Power of Data with Scylla "We were looking for something really specific. A highly scalable, and high performance NoSQL database. The answer was simple, ScyllaDB is a better fit for our use case." João Pedro Voltani
MongoDB Versus ScyllaDB, in Production at Numberly "We are happy users of both, because we select the use cases based on their strengths" We use ScyllaDB for real-time and latency sensitive pipelines, mixed batch and real-time workloads, and web backends in GraphQL (imposing a schema). We see a trend into ScyllaDB today. Alexys Jacob Numberly adoption MongoDB OSS (AGPL) MongoDB 1.4 stable Cassandra OSS (Apache) MongoDB is very strong in web backends and real time queries over unpredictable behavioral data. We need to query and operate on top of this data. This is where MongoDB flexibility is good for us. Cassandra 1.0 Cassandra 2.0 Cassandra 3.0 ScyllaDB OSS (AGPL) ScyllaDB 1.0 ScyllaDB 2.0 ScyllaDB 3.0 2016 2017 2018 2019 2015 2013 2011 2010 2008 2009 MongoDB 2.0 MongoDB 3.0 WiredTiger (3.2) MongoDB 4.0 (SSPL) MongoDB 4.2 Numberly adoption MongoDB 3.6
Takeaways 30 ■ ScyllaDB is the database for Performance ■ ScyllaDB and MongoDB are different databases ■ Knowing the differences is key for a successful transition ■ Identify the optimal data model ■ Follow a query-driven & performance-oriented design approach ■ Both have a large driver and connectors ecosystem ■ The path for migration is straightforward, and we're here to help! ■ Customers met their Performance challenges with ScyllaDB
Stay in Touch Felipe Cardeneti Mendes felipemendes@scylladb.com @cardeneti82118 @fee-mendes Find me on LinkedIn! Pete Aven pete.aven@scylladb.com @peteaven @wpaven Find me on LinkedIn!

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MongoDB to ScyllaDB: Technical Comparison and the Path to Success

  • 1. MongoDB vs ScyllaDB: Path to Success Felipe Mendes, Solution Architect at ScyllaDB Pete Aven, Solution Architect at ScyllaDB
  • 2. Meet The Team Felipe Cardeneti Mendes ■ Published Author ■ ScyllaDB Committer ■ IT Specialist & Solution Architect Your photo goes here, smile :) Pete Aven ■ Data Engineer ■ Application Development ■ ScyllaDB Solution Architect
  • 3.
  • 6. Lower Node Count Efficient hardware usage results in direct savings Where Do You Wanna Be? Predictable, Low Latencies Consistent single-digit millisecond p99 latencies Autonomous Self-Tuning Self-optimizing, smaller footprint, easy to use Always-On Architecture Active-active deployments for mission-critical workloads
  • 8. Data Model & Query Language ■ MQL – Mongo Query Language ■ Documents stored in BSON format ■ Schemaless ■ Favors Query Flexibility over Performance
  • 9. Data Model & Query Language ■ CQL or DynamoDB API ■ Wide-Column Representation ■ Schema-oriented ■ Favors Performance over Query Flexibility
  • 10. MongoDB – Replica Sets Reads Reads (optional) Reads (optional) REPLICA SET 3x replication ■ Primary-Secondary ■ Impact on Write Throughput ■ Election on Failure ■ Scaling Limitations ■ Up to 50 members ■ Arbiters ■ Non-voting members ■ Limited Storage/Replica* ■ Affect Reads Scaling MongoDB Atlas *
  • 11. MongoDB – Sharded Cluster ■ A Shard is a Replica Set ■ Adds Overhead & Complexity ■ Further Availability Concerns ■ Underutilized Capacity ■ Sharding ■ Performed Manually ■ Hashed vs Ranged ■ Still Require a Query Router Reads SHARDED CLUSTER 3 shards, 3x replication
  • 12. ScyllaDB – Sharding & Replication ■ Simplified Architecture ■ Equal Nodes ■ Sharded to the Core ■ Maximizes Infrastructure Power ■ Unlimited Scale ■ Always-On ■ No Limits ■ Fully Autonomous App App
  • 13. Independent Benchmark Results "ScyllaDB outperforms MongoDB in 132 of 133 measurements." – Daniel Seybold, benchANT CTO Read the full report
  • 14. "MongoDB is Web Scale" "The scalability results demonstrate that ScyllaDB achieves up to near linear scalability, while MongoDB shows less efficient horizontal scalability." – Daniel Seybold, benchANT CTO Read the full report
  • 16. It’s a Simple Matter of Programming(™)
  • 19. Mental Exercise MemeGroup [ { id: simpsons, title: 'The Simpsons', author: uid1, tags: ['homer', 'liza'], photos: [pid1, pid2], views: 200 } { id: comics, title: 'Comics', author: uid2, tags: ['drawing', 'cartoon'], photos: [pid1, pid2, pid3], views: 300 } { id: matrix, title: 'Matrix', author: uid1, tags: ['neo', 'morpheus', 'pill'], photos: [pid4, pid5], views: 50 } ] Memes [ { id: homer_grass, title: 'Homer Hiding', location: p1, tags: ['hiding', 'grass'], likes: 30, views: 200 } { id: morpheus_pill, title: Choose Destiny', location: p2, tags: ['pills'], likes: 99, views: 300 } { id: trollface, title: 'Troll face', location: p3, tags: ['troll', 'face], likes: 9999999, views: NaN } ] ■ Queries: ■ Display all Memes posted by a given Author, sorted by time ■ Retrieve all Groups of Memes matching a particular Tag
  • 20. Mental Exercise ■ Queries: ■ Display all Memes posted by a given Author, sorted by time ■ Retrieve all Groups of Memes matching a particular Tag CREATE TABLE MemeByAuthor ( author uuid, meme_id uuid, post_time timeuuid, title text, tags frozen<set<text>>, path text, PRIMARY KEY(author, post_time) ) CREATE TABLE MemeGroup ( group_id uuid, author_id uuid, title text, tags set<text>, memes uuid, PRIMARY KEY(group_id, memes) ) CREATE INDEX ON MemeGroup(tags); Adapted from StackOverflow
  • 21. ScyllaDB JSON Support INSERT INTO mytable JSON '{ ""_id"": 1, "title": "Reservoir Dogs", "director": ...}' SELECT and INSERT statements
  • 24. Before Migrating ■ Understand the differences between a document vs wide-column ■ Denormalize and design a query-driven approach ■ Optimize your model for fast retrieval & ingestion ■ Take the opportunity to re-evaluate your access patterns! ■ Get to know the available data-types, indexes, collections and UDTs in ScyllaDB ■ Implement highly concurrent asynchronous code in your application ■ BLAST ScyllaDB – It WILL handle it!
  • 25. Migration Walkthrough ETL Application Writes & Reads Reads Forklift Historical Data Source Connector MongoDB Change Streams ScyllaDB Sink Connector Writes & Reads
  • 27. Trillions of messages 60% fewer nodes 5msp99 "We knew we were not going to use MongoDB sharding because it is complicated to use and not known for stability" 2015 – Million 2016 – Billion 2019 – Trillion Stanislav Vishnevskiy How Discord Stores Billions and Trillions of
  • 28. Unleashing the Power of Data with Scylla "We were looking for something really specific. A highly scalable, and high performance NoSQL database. The answer was simple, ScyllaDB is a better fit for our use case." João Pedro Voltani
  • 29. MongoDB Versus ScyllaDB, in Production at Numberly "We are happy users of both, because we select the use cases based on their strengths" We use ScyllaDB for real-time and latency sensitive pipelines, mixed batch and real-time workloads, and web backends in GraphQL (imposing a schema). We see a trend into ScyllaDB today. Alexys Jacob Numberly adoption MongoDB OSS (AGPL) MongoDB 1.4 stable Cassandra OSS (Apache) MongoDB is very strong in web backends and real time queries over unpredictable behavioral data. We need to query and operate on top of this data. This is where MongoDB flexibility is good for us. Cassandra 1.0 Cassandra 2.0 Cassandra 3.0 ScyllaDB OSS (AGPL) ScyllaDB 1.0 ScyllaDB 2.0 ScyllaDB 3.0 2016 2017 2018 2019 2015 2013 2011 2010 2008 2009 MongoDB 2.0 MongoDB 3.0 WiredTiger (3.2) MongoDB 4.0 (SSPL) MongoDB 4.2 Numberly adoption MongoDB 3.6
  • 30. Takeaways 30 ■ ScyllaDB is the database for Performance ■ ScyllaDB and MongoDB are different databases ■ Knowing the differences is key for a successful transition ■ Identify the optimal data model ■ Follow a query-driven & performance-oriented design approach ■ Both have a large driver and connectors ecosystem ■ The path for migration is straightforward, and we're here to help! ■ Customers met their Performance challenges with ScyllaDB
  • 31. Stay in Touch Felipe Cardeneti Mendes felipemendes@scylladb.com @cardeneti82118 @fee-mendes Find me on LinkedIn! Pete Aven pete.aven@scylladb.com @peteaven @wpaven Find me on LinkedIn!
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