In 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.
If you are developing a new distributed application or are extending an existing one with a new set of microservices, chances are you are going to need to store data in a distributed SQL database. The plethora of niche databases that have emerged over the last decade make the task of selecting a database challenging. With many databases, each with its own nomenclature and nuances to choose from, learning a new database can be a daunting task.
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This blog post was co-authored by Mikhail Bautin and Kannan Muthukkaruppan
As described in our previous post “How We Built a High Performance Document Store on RocksDB?”, YugabyteDB’s distributed document store (DocDB) uses RocksDB as its per-node storage engine. We made multiple performance and data density related enhancements to RocksDB in the course of embedding it into DocDB’s document storage layer (figure below).
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This blog post was co-authored by Mikhail Bautin and Kannan Muthukkaruppan
RocksDB is a popular embeddable persistent key-value store. First open sourced by Facebook in 2012 as a fork of the Google LevelDB project, it has been adapted over the years to a wide range of workloads including database storage engines and application data caching.
In this post, we explain our rationale for selecting RocksDB as a foundational building block for YugabyteDB.
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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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Enterprises building cloud native services are gravitating towards transactional NoSQL and globally distributed SQL databases as their next-generation transactional stores. There are at least two distinct usage patterns among these cloud native services – internet-scale transactional workloads and scale-out RDBMS workloads. They have a lot of common demands from the database they use, such as transactions/strong consistency, data modeling flexibility, ease of scaling out and fault tolerance. However, there are some notable differences between these workloads:
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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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After launching YugabyteDB in November 2017, Team YugaByte celebrated 2018 as its first full year in the market as a cloud native, transactional database company. Exhilarating is the one word that best summarizes our 2018 experience. From a product and engineering standpoint, we launched two major releases (and tens of minor releases) and saw users adopt each of the releases at an amazing pace. This story of exceeded expectations repeated itself at every other function in the company whether it be sales,
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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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