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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Welcome to another post from our ongoing series where we highlight a new feature from the latest 1.1 release! Today we are going to look at secondary indexes.
A database index is a data structure that improves the speed of data retrieval operations on a database table. Typically, databases are very efficient at looking up data by the primary key. A secondary index can be created using one or more columns of a database table,
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The team at YugaByte is excited to announce that YugabyteDB 1.1 is officially GA! You can download the latest version from our Quick Start page. New in this release:
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Apache Cassandra is a distributed open source database that can be referred to as a “NoSQL database” or a “wide column store.” Cassandra was originally developed at Facebook to power its “Inbox” feature and was released as an open source project in 2008. Cassandra is designed to handle “big data” workloads by distributing data, reads and writes (eventually) across multiple nodes with no single point of failure.
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Editor’s note: This post was originally published August 8, 2018 and has been updated as of May 28, 2020.
As we saw in ”How Does Consensus-Based Replication Work in Distributed Databases?”, Raft has become the consensus replication algorithm of choice when it comes to building resilient, strongly consistent systems. YugabyteDB uses Raft for both leader election and data replication. Instead of having a single Raft group for the entire dataset in the cluster,
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After billions of dollars in capital expenditure and reference customers in every major vertical, Google Cloud Platform has finally emerged as a credible competitor to Amazon Web Services and Microsoft Azure when it comes to enterprise-ready cloud infrastructure. While Google Cloud’s compute and storage offerings are easier to understand, making sense of its various managed database offerings is not for the faint-hearted. This post introduces app developers to the major Google Cloud database services,
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In this blog, we dive deeper into Percolator and Spanner as well as the open source databases (YugabyteDB for example) that they have inspired
DynamoDB is AWS’s NoSQL alternative to Cassandra, primarily marketed to mid-sized and large enterprises. It works best for those who require a flexible data model, reliable performance, and the automatic scaling of throughput capacity. In a nutshell, DynamoDB’s monthly cost is dictated by data storage, writes and reads. Let’s walk through a synopsis.
This post is to help developers and operations engineers understand the precise strengths and weaknesses of DynamoDB, especially when it needs to power a complex, large-scale application.
Learn the basics of database storage engines, incl. B-tree and LSM tree based storage engines that are popular in the context of modern distributed cloud apps
