Couchbase Internals
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In this session you will learn about the architecture of Couchbase and its internals. This session is a good opportunity to understand how Couchbase Server and Clients deals with distribution of the data, caching but also indexing.
After this talk you will see and clearly understand where Couchbase fits in the "CAP Theorem" and see which tradeoffs have been made by the Couchbase development team.
Simplify, then Scale the Data Model: Using a Document-Oriented Database
"Simplify, then add lightness." was Colin Chapman's advice to those seeking performance in auto racing. When deciding where to store the data behind interactive web apps, we developers can now implement such a philosophy through Document-Oriented databases like Couchbase Server. In Couchbase's document-oriented model, the primitive operations operate on data aggregates just like the Java object model behind your application.
Storage and retrieval are done with lightweight operations such as 'get' and 'set'. Indexing and querying is done with Couchbase's views to incrementally map-reduce extract document subelements on demand. Performance in development time, sub-millisecond data access and massive scale come together in this formula.
YOU MAY ALSO LIKE:
- Real World Kotlin Development Workshop (in London on 22nd - 23rd October 2019)
- Migrating to Java 11 with Ben Evans (in London on 28th - 29th October 2019)
- Scala eXchange London 2019 (in London on 12th - 13th December 2019)
- Keynote by Luca Mezzalira on Demystifying Micro-Frontends (in London on 23rd September 2019)
- How Open Source is Funded & Privacy Engineering for the World of Kafka (in London on 24th September 2019)
- Scaling Systems: Implementations that Grow (SkillsCast recorded in September 2019)
- Neo4j (SkillsCast recorded in September 2019)
Thanks to our sponsors
Couchbase Internals
Perry Krug
Perry Krug is a Sr. Solutions Architect for Couchbase. Perry has worked with hundreds of deployments of Couchbase's NoSQL database technology. He has over 6 years of experience in high performance caching and database systems.
Please log in to watch this conference skillscast.
In this session you will learn about the architecture of Couchbase and its internals. This session is a good opportunity to understand how Couchbase Server and Clients deals with distribution of the data, caching but also indexing.
After this talk you will see and clearly understand where Couchbase fits in the "CAP Theorem" and see which tradeoffs have been made by the Couchbase development team.
Simplify, then Scale the Data Model: Using a Document-Oriented Database
"Simplify, then add lightness." was Colin Chapman's advice to those seeking performance in auto racing. When deciding where to store the data behind interactive web apps, we developers can now implement such a philosophy through Document-Oriented databases like Couchbase Server. In Couchbase's document-oriented model, the primitive operations operate on data aggregates just like the Java object model behind your application.
Storage and retrieval are done with lightweight operations such as 'get' and 'set'. Indexing and querying is done with Couchbase's views to incrementally map-reduce extract document subelements on demand. Performance in development time, sub-millisecond data access and massive scale come together in this formula.
YOU MAY ALSO LIKE:
- Real World Kotlin Development Workshop (in London on 22nd - 23rd October 2019)
- Migrating to Java 11 with Ben Evans (in London on 28th - 29th October 2019)
- Scala eXchange London 2019 (in London on 12th - 13th December 2019)
- Keynote by Luca Mezzalira on Demystifying Micro-Frontends (in London on 23rd September 2019)
- How Open Source is Funded & Privacy Engineering for the World of Kafka (in London on 24th September 2019)
- Scaling Systems: Implementations that Grow (SkillsCast recorded in September 2019)
- Neo4j (SkillsCast recorded in September 2019)
Thanks to our sponsors
Couchbase Internals
Perry Krug
Perry Krug is a Sr. Solutions Architect for Couchbase. Perry has worked with hundreds of deployments of Couchbase's NoSQL database technology. He has over 6 years of experience in high performance caching and database systems.