Editor’s note – This is the first part of a two-part series on database storage engines:
When evaluating operational databases, developers building distributed cloud applications tend to focus on data modeling flexibility, consistency guarantees, linear scalability,
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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 take into account.
Monolithic databases, which are primarily relational/SQL in nature, support strong consistency and ACID transactions.
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YugabyteDB is an open source, transactional, high-performance database for your business-critical data —and it is compatible with the Redis API. Over the years, many of us fell in love with the simplicity and the intuitiveness of the various Redis commands and data structures. We are excited to share the same love with all the Redis developers out there.
When using your Redis application with YugabyteDB, your data is replicated and persisted with strong consistency.
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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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