Bringing Truth to Competitive Benchmark Claims – YugabyteDB vs CockroachDB, Part 2
In part 1 of this blog series, we highlighted multiple factual errors in the Cockroach Labs analysis of YugabyteDB. In this second post we provide the next layer of detail behind YugabyteDB’s architecture, with an emphasis on comparing it to that of CockroachDB’s.
Contents of this post
- TLDR
- Query layer – reusing PostgreSQL
- Storage layer – engineered for performance at scale
- A deep dive into performance at large data sizes
- Results at a glance
- Take one – loading 1 billion rows with 64 threads
- CockroachDB: data load slowdown with data size increase
- Using multiple disks for a single large table
- Ranges vs tablets – architectural differences
- Impact of compactions on query performance
- YugabyteDB: 1B data load completed successfully
- Backpressure user requests when overloaded
- Take two – loading 450 million rows with 32 threads
- Detailed YCSB results
- Understanding performance in distributed SQL
- Conclusion
TLDR
Yugabyte SQL is based on a reuse of PostgreSQL’s native query layer.
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