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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Lots has happened since our last engineering update about 3 months ago. Below are some of the highlights.
We have made a lot of progress on YSQL, the PostgreSQL compatible distributed SQL API for YugabyteDB! You can also read about YSQL architecture which covers how distributed SQL is implemented in YugabyteDB.
We were at the first ever PostgresConf Silicon Valley in October 2018.
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This post aims to help application developers understand the choice of SQL vs. NoSQL in the context of the data modeling needs of an application.
This post describes how you can run Presto queries on YCQL API as well as join data across the YCQL and YSQL APIs.
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.
In this post, we will look at the architecture of YSQL, the PostgreSQL-compatible distributed SQL API in YugabyteDB. We will also touch on the current state of the project and the next steps in progress. Here is a quick overview:
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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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Prof. Daniel Abadi, lead inventor of the Calvin transaction management protocol and the PACELC theorem, wrote a thought-provoking post last month titled “NewSQL database systems are failing to guarantee consistency, and I blame Spanner”. The post takes a negative view of software-only Google Spanner derivative databases such as YugabyteDB and CockroachDB that use Spanner-like partitioned consensus for single shard transactions and a two phase commit (2PC) protocol for multi-shard (aka distributed) ACID transactions.
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Welcome to another post in our ongoing series that highlights new features from the latest 1.1 release announced last week. Today we are going to look at document data modeling using the native JSON data type available in YugabyteDB’s Cassandra compatible YCQL API. Note that this data type is specific to YugabyteDB and is not part of the standard Cassandra Query Language (CQL).
With YugabyteDB’s native JSON support,
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