A Busy Developer’s Guide to Database Storage Engines — The Basics
Learn the basics of database storage engines, incl. B-tree and LSM tree based storage engines that are popular in the context of modern distributed cloud apps
Learn the basics of database storage engines, incl. B-tree and LSM tree based storage engines that are popular in the context of modern distributed cloud apps
In the first post of this two-part series, we learned about the B-tree vs LSM approach to index management in operational databases. While the indexing algorithm plays a fundamental role in determining the type of storage engine needed, advanced considerations highlighted below are equally important to consider.
Monolithic databases, which are primarily relational/SQL in nature, support strong consistency and ACID transactions.
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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 YugabyteDB provides strong consistency while outperforming an eventually consistent DB like Apache Cassandra. Note that YugabyteDB retains drop-in compatibility with the Cassandra Query Language (CQL) API.
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