As 2022 comes to an end, organizations will continue to shift their focus from using monolithic solutions to distributed SQL databases that better align with their cloud native architectures. And that is not the only shakeup we expect to see in the new year!
Check out our top 2023 database predictions based on trends we already see taking shape.
The YugabyteDB community is at the heart of everything we do at Yugabyte. The worldwide community of open source enthusiasts, application builders, and database aficionados has been a fountain of inspiration, knowledge, and belonging for us. Here are some community highlights we’d love to call out.
We planned to celebrate when we reached 5,000 YugabyteDB Community Slack members. But then we blinked and realized we were already over 5,500!
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Distributed clock synchronization is critical for many applications, including distributed SQL databases. Clock synchronization needs to keep up with the other demands in our modern infrastructure, such as:
A distributed SQL database is highly available and resilient to failures when deployed across a cluster of nodes.
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The last decade has seen a rise in usage of distributed SQL databases for transactional, cloud native applications. Popular options include Amazon Aurora, Google Spanner, YugabyteDB, and CockroachDB. All of these databases are resilient to failures and achieve high availability. However, they vary dramatically in the set of relational database management system (RDBMS) features they support.
Google Spanner and CockroachDB have chosen to rewrite the SQL engine from scratch. As a result, they do not implement many of the advanced features supported by a traditional RDBMS.
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YugabyteDB just turned 5 years old, and I cannot help but reminisce about our journey in building this database over the last half-decade. I vividly remember the genesis of the YugabyteDB project, which started with Kannan, Mikhail, and myself meeting for lunch at a restaurant to discuss the future of cloud native databases. After iterating on the idea over a number of such discussions,
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The YugabyteDB 2.5 release adds many critical enterprise-grade security features. This blog post outlines these newly added features.
The first notable addition is the addition of a much improved, password-based authentication mechanism called Salted Challenge Response Authentication Mechanism (or simply SCRAM) as described in RFC5802. This scram-sha-256 authentication mechanism, identical to the most secure PostgreSQL authentication schema,
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We are excited to announce the availability of row-level geo-partitioning in YugabyteDB, a feature heavily requested by our user community and enterprise customers alike. This feature allows fine-grained control over pinning data in a user table (at a per-row level) to geographic locations, thereby allowing the data residency to be managed at the database level.
Making the nodes of a multi-region database cluster aware of the location characteristics of the data they store allows conforming to regulatory compliance requirements such as GDPR by keeping the appropriate subset of data local to different regions,
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Our mission at Yugabyte is to build the default distributed SQL database for cloud native applications in a multi cloud world. To further that mission, this release brings major enhancements to multi-region deployments, performance, and security features offered by the database – while simultaneously improving on high availability, horizontal scalability, and ease of managing the database.
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In two weeks, thought leaders, database builders, and application developers are coming together for a free online conference to push the boundaries of cloud native RDBMS forward. Distributed SQL (Virtual) Summit, now in its second year, is taking place September 15-17.
We’re excited to announce that the 2020 Distributed SQL Summit schedule is now live!
Speakers include:
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Getting total row counts of data in tables across various dimensions (per-table, per-schema, and in a given database) is a useful technique to have in one’s tool belt of SQL tricks. While there are a number of use cases for this, my scenario was to get the per-table row counts of all tables in PostgreSQL and YugabyteDB as a first sanity check after migrating an application with the pre-existing data from PostgreSQL to YugabyteDB.
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