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Introduction to Cassandra Versions

Hadoop, Data Science, Statistics & others

Apache Cassandra was developed by Avinash Lakshman and Prashant Malik at Facebook to power its search inbox feature. Facebook then released Cassandra as an open-source project on Google code and in 2008 and in 2009 it became an Apache Incubator project. In 2010 it launched as a top-level project becoming a part of the Apache Software Foundation.

Top 11 Versions of Cassandra

Following are the Cassandra versions are given below:

1. Version 0.6 (April ‘10)

This was the launch of Apache Cassandra after being in development phase and graduating from Apache Incubator and becoming part of the Apache Software Foundation meaning receiving full support from Apache Foundation. It incorporated support for Hadoop, caching, and improved performance. The Hadoop support allowed Cassandra to use MapReduce framework to run various analyses on data stored within Cassandra. This change simply changed the architecture for good and boosted overall performance and use cases.

2. Version 0.7 (Jan ’11) 3. Version 0.8 (June ‘11)

This was a major update where CQL for Cassandra Query Language was introduced along with other updates like self-tuning memtables and support for zero-downtime upgrades. In this update, Cassandra offered CQL, which closely modeled after SQL where data was stored in tables containing rows and columns.

4. Version 1.0 (Oct ‘11) 5. Version 1.1 (April ‘12) 6. Version 1.2 (Jan ‘13)

This version added clustering across Virtual Nodes which improve the granularity of capacity increases and dramatically improved

repair and rebuild time in larger clusters, CQL3 improvement, notably the addition of collection types, Queryable system information and CQL Native protocol and, Atomic batches addressing the possibility of mid batch coordinator failure amongst other performance improvements.

7. Version 2.0 (September ‘13)

Cassandra 2.0 came with some of the most evolutionary upgrades like making it easier for developers to migrate from a relational database and become more productive. Some of the other improvements with 2.0 were,

Lightweight transactions that were based on Paxos consensus protocol ensured an operation linearization which is similar to the serializable isolation level offered by relational databases that prevent conflicts during concurrent requests.

Triggers which enable pushing performance-critical code close to the data it deals with and also simplifying integration with an event-driven framework like Apache Storm.

8. Version 2.1, 2.2 (September ‘14)

This was an incremental update where apart from Performance upgrades some other features included improved Hadoop Support, Post compaction read performance, incremental node repair, improved row cache.

9. Version 3.0 (November ‘15) 10. Version 3.1 – 3.10 (2023-17)

There were monthly releases where updates were done through tick-tock like release model, with even-numbered releases providing both new features and bug fixes while odd-numbered releases would only have bug fixes.

11. Version 3.11 (June ‘17)

This is the latest stable release of Cassandra till date. It brought along with it some minor bug fixes and overall performance improvements. Version 4 of Apache Cassandra is expected to be released anytime this year with some major incremental changes.

Conclusion

Cassandra has come a long way and countless iterations over the years and is used today y organizations like CERN, Apple, Netflix, and various governmental institutions. It is imperative for anyone interested in the field of Big data to be aware of NoSQL databases like Apache Cassandra along with other technologies like Hadoop and Spark which are used together to have a holistic understanding of Data Science in general and Big data in particular.