The YugaByte Database Blog

Thoughts on open source, cloud native and distributed databases

Achieving Sub-ms Latencies on Large Datasets in Public Clouds

One of our users was interested to learn more about YugaByte DB’s behavior for a random read workload where the data set does not fit in RAM and queries need to read data from disk (i.e. an uncached random read workload).

The intent was to verify if YugaByte DB was designed well to handle this case with the optimal number of IOs to the disk subsystem.

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Scaling YugaByte DB to Millions of Reads and Writes

Here at YugaByte, we continuously push the limits of the systems we build. As a part of that, we ran some large cluster benchmarks to scale YugaByte DB to million of reads and writes per second while retaining low latencies. This post goes into the details about our 50 node cluster benchmark. We posted the results of the benchmark on a 25 node cluster in our community forum.

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Building a Strongly Consistent Cassandra with Better Performance

In an earlier blog on database consistency, we had a detailed discussion on the risks and challenges applications face in dealing with eventually consistent NoSQL databases. We also dispelled the myth that eventually consistent DBs perform better than strongly consistent DBs. In this blog, we will look more closely into how YugaByte DB provides strong consistency while outperforming an eventually consistent DB like Apache Cassandra.

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YugaByte DB Architecture: Diverse Workloads with Operational Simplicity

YugaByte DB is a transactional, high performance, geo-distributed operational database that converges multiple NoSQL and SQL interfaces into an unified solution. The v0.9 public beta of YugaByte DB is compatible with Apache Cassandra (CQL) and Redis APIs, with PostgreSQL under development. A fundamental design goal for YugaByte DB has been to provide the same transactional, performance and operational simplicity guarantees irrespective of the API used.

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