Apache Cassandra 5.0: Answering Enterprises' Biggest Questions

By Bassam Chahine, Instaclustr by NetApp

With the general availability of Apache Cassandra 5.0 fast approaching, I'm receiving more questions than ever from Cassandra users wondering how upgrading their version of the open source NoSQL database might benefit their specific use cases.

So in honor of Cassandra's fifth version, let's count down the top-five most pressing questions users have right now — along with my answers and perspective.

5) "What does Cassandra 5.0 offer that previous versions don't?"

Even more so than previous releases, Cassandra 5.0 is especially future-oriented and focused on enabling modern use cases.

The huge answer to "what's new" is that Cassandra 5.0 is fully ready to support enterprise goals and requirements around AI development (a subject I'll cover in more detail in later questions). New features like vector search and storage-attached indexing (SAI) make it simpler to build LLMs and perform the advanced data analysis required to achieve (accurate) AI-powered experiences.

SAI and Cassandra 5.0's new unified compaction strategy optimizes resource usage to improve overall efficiency and performance — especially in the area of data management and retrieval. The new version also introduces trie-based memtables and SSTables, which specifically optimize efficiency for storage and read/write operations.

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Want more? Cassandra 5.0 brings unprecedented security and flexibility. The introduction of dynamic data masking (DDM) masks sensitive data to prevent unauthorized access. The new version's experimental support for JDK 17 lets users take advantage of Java's newest features and performance and security improvements (although JDK 17 isn't recommended for use in production quite yet). Cassandra 5.0's new mathematical CQL functions also give developers more flexibility to complete complex data operations and make applications more performant.

4) "Can I upgrade my Cassandra 3.x workload to Cassandra 5.0?"

It's not uncommon for enterprises to delay upgrades to their critical data layer infrastructure in the name of trust and stability, even if it means leaving new features and efficiencies on the table.

Unfortunately, for users running a Cassandra 3.x cluster, it's only possible to upgrade Cassandra by one major version release at a time. That means these users' clusters will have a layover at Cassandra 4.x — ideally the latest 4.1.4 release — on their trip to Cassandra 5.0.

3) "Why should I upgrade?"

The features I've mentioned — vector search, SAI, unified compaction strategy, and others — offer significant benefits in the areas of reducing storage expenses, increasing performance, and developing AI applications. Cassandra 5.0's increased stability via bug fixes and added support for guardrails should further entice enterprise users to make the upgrade.

But there's also a stick that comes with those carrots: The general release of Cassandra 5.0 coincides with the end of life for Cassandra 3.0 and 3.11. While managed providers may extend support for these versions to make sure enterprises can migrate on their terms (in our case we're extending such support for one year), the writing is on the wall that it's time to move forward. If a migration is in the cards regardless, it makes sense for enterprises to upgrade to the latest and greatest.

2) "Will Cassandra 5.0 save me money?"

The quick answer is yes: Cassandra 5.0 puts enterprises in position to better manage their infrastructure and reduce operational expenses. Specifically, SAIs use index and query data more efficiently, requiring fewer resources in read operations. Depending on the use case, enterprises may be able to leverage equal performance using smaller clusters or node types. With the unified compaction strategy automating and optimizing Cassandra 5.0's compaction process, compactions require less storage and I/O overhead, again improving performance and reducing operational costs.

1) "How does Cassandra 5.0 help us reach our AI goals?"

Most enterprises have big AI ambitions right now (as well they should), and they need a powerful infrastructure for harnessing intelligent data. Cassandra 5.0 is quickly emerging as an ideal candidate for that role, with its capabilities as a vector database, new vector functions, and SAIs easily handling complex high-dimensional data at scale.

As a full-featured vector database, Cassandra now positions enterprises to implement LLMs, generative AI, Retrieval-Augmented Generation (RAG), Natural Language Processing (NLP), and Geographical Information Systems (GIS) applications. Vector search enables the advanced data analysis, creative content generation, semantic search, and spatial analysis those processes require to thrive.

Well Worth the Price of Adoption

Open source Apache Cassandra is still what it's always been: a highly available, scalable, reliable, and performant free and open source data layer option. Cassandra 5.0 makes it all those things and more, with valuable improvements to operational efficiency, flexibility, and powerful new capabilities for supporting AI workloads. Enterprises with experience benefiting from Cassandra should only expect those benefits to grow as they adopt this latest version.

About the author:

Bassam Chahine is a Principal Consultant at Instaclustr by NetApp. Bassam joined Instaclustr from Intuit, where he held several database engineering and database administration roles over his 15-plus years with the company.