Data Sharding

December 14, 2022

Q&A: Partitioning vs Sharding, Scaling Behavior, and Visualization Tools for YugabyteDB

Welcome to the December 2022 edition of the YugabyteDB Tips and Tricks series, where we recap distributed SQL database questions from around the Internet! This month we will focus on the differences between table partitioning and sharding in a distributed SQL deployment, whether or not the scaling limitations in RocksDB has an impact on YugabyteDB, and tools for visualizing the data stored in the Yugabyte database.

How to Avoid Hotspots on Range-based Indexes in Distributed Databases

November 15, 2022

By Premkumar Thangamani

Distributed SQL How To YugabyteDB

How to Avoid Hotspots on Range-based Indexes in Distributed Databases

Some data model choices in distributed databases cause data to grow in one node before it moves to another node. This will cause one node to become a hotspot for reads and writes. This article explains how to avoid that.

Tablet Splitting, High Availability Behavior, & Sharding vs Partitioning with YugabyteDB

September 28, 2022

By Marko Rajcevic

Distributed SQL YugabyteDB

Tablet Splitting, High Availability Behavior, & Sharding vs Partitioning with YugabyteDB

Welcome to the September 2022 edition of the YugabyteDB Tips and Tricks series, where we recap distributed SQL database questions from around the Internet! This month we will focus on recommended values for tablet splitting, behavior around high availability, client behavior when a node goes down, and sharding versus partitioning of a table.

Distributed SQL Sharding: How Many Tablets and at What Size?

June 17, 2022

By Franck Pachot

Distributed SQL How It Works

Distributed SQL Sharding: How Many Tablets and at What Size?

Explore how database sharding works, how to handle corner cases correctly, and how to split tablets to save resources.

Distributed SQL: Sharding and Partitioning in YugabyteDB

November 19, 2021

By Franck Pachot

Databases Distributed SQL

Distributed SQL: Sharding and Partitioning in YugabyteDB

A distributed SQL database provides a service where you can query the global database without knowing where the rows are. You connect to any node, without having to know the cluster topology. You query your tables, and the database will determine the best access to your data, whether it’s close to your client or geographically distant.

The organization of data, whether co-located or partitioned, is the most important consideration for high performance,

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Distributed SQL Tips and Tricks – Feb 21, 2020

February 21, 2020

By Dorian Hoxha

Databases Distributed SQL Google Spanner How To PostgreSQL

Distributed SQL Tips and Tricks – Feb 21, 2020

Welcome to this week’s tips and tricks blog where we recap some distributed SQL questions from around the Internet. We’ll also review upcoming events, new documentation, and blogs that have been published since the last post. Got questions? Make sure to ask them on our YugabyteDB Slack channel, Forum, GitHub, or Stackoverflow. Ok, let’s dive right in:

When should I use JSON vs JSONB data types?

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Four Data Sharding Strategies We Analyzed in Building a Distributed SQL Database

January 14, 2020

By Karthik Ranganathan

Distributed SQL How It Works YugabyteDB

Four Data Sharding Strategies We Analyzed in Building a Distributed SQL Database

A distributed SQL database needs to automatically partition the data in a table and distribute it across nodes. This is known as data sharding and it can be achieved through different strategies, each with its own tradeoffs. In this post, we will examine various data sharding strategies for a distributed SQL database, analyze the tradeoffs, explain the rationale for which of these strategies YugabyteDB supports and what we picked as the default sharding strategy.

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How Data Sharding Works in a Distributed SQL Database

June 6, 2019

By Sid Choudhury

Distributed SQL How It Works YugabyteDB

How Data Sharding Works in a Distributed SQL Database

Editor’s note: This post was updated August 28, 2020 to include new sharding features available starting in YugabyteDB 2.2

Enterprises of all sizes are embracing rapid modernization of user-facing applications as part of their broader digital transformation strategy. The relational database (RDBMS) infrastructure that such applications rely on suddenly needs to support much larger data sizes and transaction volumes. However, a monolithic RDBMS tends to quickly get overloaded in such scenarios.

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Overcoming MongoDB Sharding and Replication Limitations with YugabyteDB

March 7, 2018

By Sid Choudhury

How It Works MongoDB YugabyteDB

Overcoming MongoDB Sharding and Replication Limitations with YugabyteDB

Although MongoDB has made significant improvements in its sharding and replication architecture since its origins as an Available and Partition-tolerant (AP) database, it still has limitations that make it unsuitable for highly scalable and latency-sensitive applications. In this blog post, the authors explore the reasons why some users have chosen to switch from MongoDB to YugabyteDB, citing distributed ACID transactions and better scalability as key factors.

Data Sharding

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