Setting The Stage For The Next Chapter Of The Cassandra Database
Data Engineering Podcast
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Cassandra
Cassandra is primarily used as a system of record because of the durability guarantees. It's able to be fault tolerant at both the cluster scale and the geographic scale. Debesium essentially allows you to grab that sedy seed data from a stream, jump it into a catcuundor. And i think that's superimportant to get your transactional darty kind of usage in place.
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Summary
The Cassandra database is one of the first open source options for globally scalable storage systems. Since its introduction in 2008 it has been powering systems at every scale. The community recently released a new major version that marks a milestone in its maturity and stability as a project and database. In this episode Ben Bromhead, CTO of Instaclustr, shares the challenges that the community has worked through, the work that went into the release, and how the stability and testing improvements are setting the stage for the future of the project.
Announcements
- Hello and welcome to the Data Engineering Podcast, the show about modern data management
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- Your host is Tobias Macey and today I’m interviewing Ben Bromhead about the recent release of Cassandra version 4 and how it fits in the current landscape of data tools
Interview
- Introduction
- How did you get involved in the area of data management?
- For anyone who isn’t familiar with Cassandra, can you briefly describe what it is and some of the story behind it?
- How did you get involved in the Cassandra project and how would you characterize your role?
- What are the main use cases and industries where someone is likely to use Cassandra?
- What is notable about the version 4 release?
- What were some of the factors that contributed to the long delay between versions 3 and 4? (2015 – 2021)
- What are your thoughts on the ongoing utility/benefits of projects such as ScyllaDB, particularly in light of the most recent release?
- Cassandra is primarily used as a system of record. What are some of the tools and system architectures that users turn to when building analytical workloads for data stored in Cassandra?
- The architecture of Cassandra has lent itself well to the cloud native ecosystem that has been growing in recent years. What do you see as the opportunities for Cassandra over the near to medium term as the cloud continues to grow in prominence?
- What are some of the challenges that you and the Cassandra community have faced with the flurry of new data storage and processing systems that have popped up over the past few years?
- What are the most interesting, innovative, or unexpected ways that you have seen Cassandra used?
- What are the most interesting, unexpected, or challenging lessons that you have learned while working on Cassandra?
- When is Cassandra the wrong choice?
- What is in store for the future of Cassandra?
Contact Info
- @benbromhead on Twitter
- benbromhead on GitHub
Parting Question
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
Links
- Cassandra
- Instaclustr
- HBase
- DynamoDB Whitepaper
- Property Based Testing
- QuickTheories
- Riak
- FoundationDB
- ScyllaDB
- YugabyteDB
- Azure CosmoDB
- Amazon Keyspaces
- Netty
- Kafka
- CQRS == Command Query Responsibility Segregation
- Elasticsearch
- Redis
- Memcached
- Debezium
- CDC == Change Data Capture
- Bigtable White Paper
- CockroachDB
- Vitess
- CAP Theorem
- Paxos
The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
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