Welcome 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. Ok, let’s dive right in:
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We 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. YugabyteDB’s SQL API (YSQL) and drivers are PostgreSQL wire compatible
TLS encryption is now supported between yb-master and yb-tserver processes.
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If a partial index is used, instead of a regular one, on a nullable column—where only a small fraction of the rows have not null values for this column—then the response time for inserts, updates, and deletes can be shortened significantly. As a bonus, the response times for single row selects shorten a little bit too. This post explains what a partial index is, shows how to create one, describes the canonical use case that calls for a partial index,
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There 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). This post details the results of this experiment as well as highlights the key aspects of the YugabyteDB architecture that makes it fit for such high-volume ingest workloads.
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In this blog post we’ll be focusing on PostgreSQL data types, and test their compatibility with YugabyteDB. You can find a quick list of supported data types in our docs.
Welcome 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. Ok, let’s dive right in:
AndrewLiuRM over on the forums asked why the yb-ctl command doesn’t give node information when issued after a manual deployment onto a Docker container.
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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 a high-latency, unreliable Wide Area Network (WAN) are minimized.
Before 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), and these can appear slightly different in both tables.
Fuzzy String Matching (or Approximate String Matching) is the process of finding strings that approximately match a pattern.
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We are pleased to announce that YugabyteDB 2.0.1 is live! You can read the release notes of this and previous versions here. This release is shipping with 36 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. Yugabyte’s SQL API (YSQL) and drivers are PostgreSQL wire compatible
With the YCQL API,
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Well, 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, 2019.
If you couldn’t make it out to this year’s event, have no fear!
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