The Distributed SQL Blog

May 21, 2018

Community News Distributed SQL How It Works Release Announcements

YugabyteDB 1.0 — A Peek Under The Hood

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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May 2, 2018

By Kannan Muthukkaruppan

Release Announcements

Announcing YugabyteDB 1.0!

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.

The Inspiration

Modern user-facing applications are increasingly moving to a multi-region,

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Distributed ACID Transactions with High Performance

April 24, 2018

By Karthik Ranganathan

ACID Transactions Databases Distributed SQL Google Spanner How It Works Performance Benchmarks

Distributed ACID Transactions with High Performance

ACID transactions are a fundamental building block when developing business-critical, user-facing applications. They simplify the complex task of ensuring data integrity while supporting highly concurrent operations. While they are taken for granted in monolithic SQL/relational databases, distributed NoSQL/non-relational databases either forsake them completely or support only a highly restrictive single-row flavor (see sections below). This loss of ACID properties is usually justified with a gain in performance (measured in terms of low latency and/or high throughput).

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Orchestrating Stateful Apps with Kubernetes StatefulSets

April 17, 2018

By Sid Choudhury

How It Works How To Kubernetes

Orchestrating Stateful Apps with Kubernetes StatefulSets

Kubernetes, the open source container orchestration engine that originated from Google’s Borg project, has seen some of the most explosive growth ever recorded in an open source project. The complete software development lifecycle involving stateless apps can now be executed in a more consistent, efficient and resilient manner than ever before. However, the same is not true for stateful apps — containers are inherently stateless and Kubernetes did not do anything special in the initial days to change that.

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Overcoming MongoDB Sharding and Replication Limitations

March 7, 2018

By Sid Choudhury

How It Works MongoDB YugabyteDB

Overcoming MongoDB Sharding and Replication Limitations

MongoDB’s sharding and replication have improved since it was first an AP database, but it still has limitations for highly scalable and latency-sensitive apps. In this blog, the authors discuss why users switch to YugabyteDB due to distributed ACID transactions and improved scalability.

Building Scalable Cloud Services — An Instant Messaging App

February 2, 2018

By Karthik Ranganathan

How To

Building Scalable Cloud Services — An Instant Messaging App

Explore building a chat app with YugabyteDB, a transactional cloud database. This series begins with a scalable Facebook Messages-like application, leveraging YugabyteDB’s capabilities to handle complex chat functionalities efficiently and effectively. Stay tuned for detailed insights and practical examples in our upcoming posts.

Achieving Sub-ms Latencies on Large Datasets in Public Clouds

January 26, 2018

By Kannan Muthukkaruppan

Amazon Web Services Cloud Providers Google Cloud Platform How It Works Microsoft Azure Performance Benchmarks

Achieving Sub-ms Latencies on Large Datasets in Public Clouds

One of our users was interested to learn more about YugabyteDB’s behavior for a random read workload where the data set does not fit in RAM and queries need to read data from disk (i.e. an uncached random read workload).

The intent was to verify if YugabyteDB was designed well to handle this case with the optimal number of IOs to the disk subsystem.

This post is a sneak peak into just one of the aspects of YugabyteDB’s innovative storage engine,

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Practical Tradeoffs in Google Cloud Spanner, Azure Cosmos DB and YugabyteDB

January 25, 2018

By Sid Choudhury

ACID Transactions Amazon Web Services Distributed SQL Google Cloud Platform Google Spanner Microsoft Azure Microsoft Azure Cosmos DB

Practical Tradeoffs in Google Cloud Spanner, Azure Cosmos DB and YugabyteDB

Updated April 2019.

The famed CAP Theorem has been a source of much debate among distributed systems engineers. Those of us building distributed databases are often asked how we deal with it. In this post, we dive deeper into the consistency-availability tradeoff imposed by CAP which is only applicable during failure conditions. We also highlight the lesser-known-but-equally-important consistency-latency tradeoff imposed by the PACELC Theorem that extends CAP to normal operations.

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Using Redis API as a True Distributed, Fault-Tolerant Database

January 18, 2018

By Karthik Ranganathan

How It Works

Using Redis API as a True Distributed, Fault-Tolerant Database

YugabyteDB’s compatibility with the Redis API enhances data replication and consistency, offering a ‘unified cache + database’ solution. It simplifies data sharding, supports large datasets without full memory reliance, and provides polyglot persistence for diverse workloads.

Scaling YugabyteDB to Millions of Reads and Writes

January 12, 2018

By Bharat Baddepudi

How It Works Performance Benchmarks

Scaling YugabyteDB to Millions of Reads and Writes

Yugabyte’s 50-node cluster benchmark demonstrates linear scalability in YugabyteDB, doubling throughput from 25 to 50 nodes with consistently low latencies. Conducted on Google Cloud Platform, these results highlight YugabyteDB’s cloud-native capabilities, applicable across various cloud and on-premise environments.

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