Thoughts on distributed databases, open source, and cloud native
Welcome back to our tips and tricks blog! I have the distinct pleasure of recapping distributed SQL questions from around the Internet for the month of December.
This ongoing series would not be possible without Dorian Hoxha, Franck Pachot, and Frits Hoogland. We also thank our incredible user community for their work with the technology.
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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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The team at Yugabyte and members of the community were excited to announce the general availability of YugabyteDB 2.0 this week. One of the flagship features of the release was the production readiness of the PostgreSQL compatible, Yugabyte SQL API (YSQL). In other blogs we covered Jepsen testing results, new performance benchmarks and ecosystem integrations including the GraphQL projects Hasura and Prisma.
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Read MoreNote: This post contains interactive animations that explain how some of these complex algorithms work. Please view this post in a suitable media (at least 1000px by 600px screen resolution) for best results.
In this blog post, we are going to dive deep into the read performance of Raft – why read performance can take a hit and how it can be improved using leader leases.
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You can join the discussion about the results on HackerNews here.
Last year we published our DIY Jepsen testing results – including the tests and failure modes implemented as well as the bugs found. We recently engaged Kyle Kingsbury, the creator of the Jepsen test suite, for an official analysis and are happy to report that YugabyteDB 1.2 formally passes Jepsen tests using the YCQL API.
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Read MoreIn the first post of our series comparing YugabyteDB with PostgreSQL and MongoDB, we mapped the core concepts in YugabyteDB to the two popular databases. This post is a deeper dive into the high availability and transactions architecture of these databases.
Almost all databases including YugabyteDB use replication to ensure that the database remains highly available under failures.
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Read MoreFoundationDB enjoys a unique spot in the transactional NoSQL space given its positioning as a basic key-value database that can be used to build new, more application-friendly databases. Given that many of the guarantees provided by its core engine (such as multi-shard ACID transactions and high fault tolerance) are similar to those provided by YugabyteDB, our users often ask us for a comparison.
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At last month’s KubeCon + CloudNativeCon in Seattle, the single biggest change from previous container-related conferences was the excitement among the end user companies around their adoption of Kubernetes and the associated cloud native infrastructure ecosystem. The CNCF End User Community page today lists 50+ enterprises and 21+ case studies including those from industry bellwethers such as Capital One,
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Read MoreThe NoSQL database revolution started with the publication of the Google BigTable and Amazon Dynamo papers in 2006 and 2007 respectively. These original designs focused on horizontal write scalability without compromising the performance observed in the single node databases dominant at that time. The compromises instead came either in the form of eventual consistency (i.e. inability to read the last update) or loss of multi-key access patterns (such as SQL integrity/foreign key constraints,
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YugaByte is excited to be at KubeCon today to announce Kubernetes StatefulSets support for our distributed SQL API which complements the transactional NoSQL APIs already generally available. YSQL is YugabyteDB’s PostgreSQL-compatible Distributed SQL API (currently in Beta). This new feature, available in YugabyteDB 1.1.7, cloud-native applications and microservices can rely on SQL and NoSQL to take full advantage of Kubernetes StatefulSets to power horizontally scalable,
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