In this blog post, we will discuss how to maintain transactional read guarantees on an async standby configured through cross cluster replication. This feature has bearing on any user who runs a transactional application in a distributed setup. We think that may apply to many people reading this blog.
YugabyteDB 2.0 is now generally available, featuring the production readiness of the PostgreSQL compatible Yugabyte SQL API (YSQL). In addition to Jepsen testing results, new performance benchmarks, and ecosystem integrations, YugabyteDB 2.0 offers a high degree of PostgreSQL compatibility, with plans for future support.
Note: 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. Additionally, we will also look at how to make the correctness guarantees around leader leases stronger.
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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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FoundationDB 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 the YugabyteDB database, our users often ask us for a comparison. These users are essentially trying to understand whether they should build their app directly using one of the three YugabyteDB APIs or should they explore/build a new database layer on FoundationDB first.
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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, Netflix, Nordstrom and Pinterest. There is a common adoption pattern among all these case studies —
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The SQL vs. NoSQL database split emerged in 2006-2007, but NoSQL’s compromises led developers to continue using SQL/RDBMS for critical workloads. However, recent changes in the NoSQL world have seen the adoption of ACID transactions, which were previously absent, and this post aims to inform architects of these changes and why they are happening now.
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, highly fault-tolerant data services,
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MongoDB’s “schemaless” JSON data modeling was initially attractive to web app developers looking to escape the constraints of traditional relational databases, but issues with data durability and ACID transactions have been a consistent challenge. While the recent MongoDB 4.0 release includes multi-document transaction support, this post explores where the platform falls short for transactional, high performance apps.
ACID transactions were a big deal when first introduced formally in the 1980s in monolithic SQL databases such as Oracle and IBM DB2. Popular distributed NoSQL databases of the past decade including Apache Cassandra initially focused on “big data” use cases that did not require such guarantees and hence avoided implementing them altogether. Our post, “A Primer on ACID Transactions: The Basics Every Cloud App Developer Must Know” details the various types of ACID transactions (single key,
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