The de-facto tool to model and test workloads on Cassandra is cassandra-stress. It is a widely known tool, appearing in numerous blog posts to illustrate performance testing on Cassandra and often recommended for stress testing specific data models. Theoretically there is no reason why cassandra-stress couldn’t fit your performance testing needs. But cassandra-stress has some caveats when modeling real workloads, the most important of which we will cover in this blog post.

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In our first post about TimeWindowCompactionStrategy, Alex Dejanovski discussed use cases and the reasons for its introduction in 3.0.8 as a replacement for DateTieredCompactionStrategy. In our experience switching production environments storing time series data to TWCS, we have seen the performance of many production systems improve dramatically.

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In this post we’ll explore a new compaction strategy available in Apache Cassandra. We’ll dig into it’s use cases, limitations, and share our experiences of using it with various production clusters.

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In this post I’ll introduce you to an advanced option in Apache Cassandra called user defined compaction. As the name implies, this is a process by which we tell Cassandra to create a compaction task for one or more tables explicitly. This task is then handed off to the Cassandra runtime to be executed like any other compaction.

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