Yugabyte helps Fortune 500 companies modernize their systems of record, which are integral to the web-based interactions of their customers. These systems require accuracy, consistency, and resiliency. Strategies like replication and sharding help maintain high availability in a cloud native world.
In this post, we shine a spotlight on Admiral’s Co-Founder, James Hartig. Read on to learn more about James’ passion for databases and the first time he heard about YugabyteDB. He also discusses his experience using YugabyteDB Managed (formerly Yugabyte Cloud) to serve 10,000 queries per second across three continents.
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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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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For ever-growing data workloads such as time series metrics and IoT sensor events, running a highly dense database cluster where each node stores terabytes of data makes perfect sense from a cost efficiency standpoint. If we are spinning up new data nodes only to get more storage-per-node, then there is a significant wastage of expensive compute resources. However, running multi-terabyte data nodes with Apache Cassandra as well as other Cassandra-compatible databases (such as DataStax Enterprise) is not an option.
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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 2, 2018 and has been updated as of May 26, 2020.
Whether it be a WordPress website’s MySQL backend or Dropbox’s multi-exabyte storage system, data replication is at the heart of making data durable and available in the presence of hardware failures such as machine crashes, disk failures, network partitions, and clock skews. The basic idea behind replication is very simple: keep multiple copies of data on physically isolated hardware so that one hardware failure does not impact the others;
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When creating a Cassandra-compatible YCQL table in the YugabyteDB database, you are required to create a primary key consisting of one or more columns of the table. Primary key based retrievals are efficient because YugabyteDB automatically indexes/organizes the data by the primary key. However, there are many use cases where you may need to retrieve data using columns that are not a part of the primary key. This is where secondary indexes help.
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Modern user-facing apps, like E-Commerce and SaaS, frequently require features from multiple databases (broadly — SQL, NoSQL and a cache) to support their multi-workload needs. App developers are responsible for understanding and managing which pieces of data should be stored in which SQL and NoSQL database. Furthermore, the app is also responsible for moving data across the tiers (e.g. populating the cache on reads and invalidating it on writes). This greatly increases development and operational complexity,
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Team YugaByte is delighted to announce the general availability of YugabyteDB 1.0!
It has been an incredibly satisfying experience to, in just two years, build and launch a cloud-scale, transactional and high-performance database that’s already powering real-world production workloads. I wanted to take a moment to share our journey to 1.0 and the road ahead.
Modern user-facing applications are increasingly moving to a multi-region,
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