Thoughts on distributed databases, open source and cloud native
We are pleased to announce that YugabyteDB 2.0.5 is live! You can read the offical release notes of this and previous versions here. This release is shipping with over 40 new enhancements and bug fixes.
What’s YugabyteDB? It is an open source, high-performance distributed SQL database built on a scalable and fault-tolerant design inspired by Google Spanner.
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Read MoreWelcome to this week’s community update where we recap a few interesting questions that have popped up in the last week or so on the YugabyteDB Slack channel, the Forum, GitHub or Stackoverflow. We’ll also review upcoming events, new blogs and documentation that has been published since the last update.
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Read MoreWe are pleased to announce that YugabyteDB 2.0.3 is live! You can read the release notes of this and previous versions here. This release is shipping with 50 new enhancements and bug fixes.
What’s YugabyteDB? It is an open source, high-performance distributed SQL database built on a scalable and fault-tolerant design inspired by Google Spanner.
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Read MoreThere are a number of well-known experiments where eventually-consistent NoSQL databases were scaled out to perform millions of inserts and queries. Here, we do the same using YSQL, YugabyteDB’s PostgreSQL-compatible, strongly-consistent, distributed SQL API. We created a 100-node YugabyteDB cluster, ran single-row INSERT and SELECT workloads with high concurrency – each for an hour and measured the sustained performance (throughput and latency).
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Read MoreIn the world of databases, data types restrict what can be considered as valid values in a table’s column. For example, if we want a column to store only integer values, we can specify that the column be an int column. Enforcing what type of data can go into a column has the added benefit of helping with storage and in some cases,
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This post is an in-depth look at the various techniques that applications needing low latency and high availability can leverage while using a geo-distributed SQL database like YugabyteDB so that the negative impacts of an high-latency, unreliable Wide Area Network (WAN) are minimized.
Enterprises are increasingly moving to cloud-native applications powered by microservices architecture.
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Read MoreBefore analyzing a large dataset that contains textual information, it’s important to scrub it and eliminate duplicates when necessary. To remove duplicates, you may need to compare strings referring to the same thing, but that may be written slightly different, have typos or were misspelled. Alternatively, you might need to join two tables on a column (let’s say on company name),
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Read MoreWell, that’s a wrap! Yugabyte would like to extend a special thanks to JD and Amanda from the Postgreconf.org team, and to all the speakers from Facebook, Google, Amazon, Pivotal, Salesforce, Narvar, Plume Design and others that presented at the first-ever Distributed SQL Summit on Sept 20,
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Read MoreTriggers are a basic feature that all monolithic SQL systems like Oracle, SQL Server and PostgreSQL have supported for many years. They are very useful in a variety of scenarios ranging from simple audit logging, to advanced tasks like updating remote databases in a federated cluster. In this blog, we’ll look at examples of INSERT, UPDATE and INSTEAD OF triggers in Yugabyte DB.
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This post addresses a concern raised about a benchmarking result we recently published comparing the performance of YugabyteDB, Amazon Aurora and CockroachDB. It was pointed out that we unfairly used the default isolation level for each database rather than use serializable isolation level in all databases (even though serializable level was not required for these workloads). In addition,
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