YugabyteDB’s compatibility with the Redis API enhances data replication and consistency, offering a ‘unified cache + database’ solution. It simplifies data sharding, supports large datasets without full memory reliance, and provides polyglot persistence for diverse workloads.
Yugabyte’s 50-node cluster benchmark demonstrates linear scalability in YugabyteDB, doubling throughput from 25 to 50 nodes with consistently low latencies. Conducted on Google Cloud Platform, these results highlight YugabyteDB’s cloud-native capabilities, applicable across various cloud and on-premise environments.
This blog highlights the challenges of handling time series data with vanilla Redis and the efficiency of YugaByte’s TS datatype
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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This post highlights the architectural considerations that went into the design of the DocDB and YQL layers for the YugabyteDB database.
Today, we are launching Yugabyte out of stealth and announcing the availability of YugabyteDB’s first public beta release.
Dive into the types of consistency referenced by the CAP theorem, learn how they impact an app, and get the facts re: common myths about eventual consistency.
Ever wondered which database Facebook (FB) uses to store the profiles of its 2.3B+ users? Is it SQL or NoSQL? How has FB database architecture evolved over the last 15+ years? As an engineer in FB database infrastructure team from 2007 to 2013, I had a front row seat in witnessing this evolution. There are invaluable lessons to be learned by better understanding the database evolution at the world’s largest social network,
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Let’s look at the evolution from RDBMSs to NoSQL databases to handle massive data and complex operations.
