Blogs by: Karthik Ranganathan

November 12, 2020

Community News Company News Databases Distributed SQL PostgreSQL Release Announcements

Announcing YugabyteDB 2.5

Support for Geo-Partitioning and Enterprise-Grade Security Features

Our mission at Yugabyte is to build the default distributed SQL database for cloud native applications in a multi cloud world. To further that mission, this release brings major enhancements to multi-region deployments, performance, and security features offered by the database – while simultaneously improving on high availability, horizontal scalability, and ease of managing the database.

Enhanced multi-region capabilities with geo-partitioning and follower reads: The YugabyteDB 2.5 release adds row-level geo-partitioning capabilities as well as follower reads to the extensive set of multi-region features that YugabyteDB already had.

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Row Counts of Tables in a SQL Schema and Database: PostgreSQL vs. YugabyteDB

August 27, 2020

By Karthik Ranganathan

Compare and contrast PostgreSQL YugabyteDB

Row Counts of Tables in a SQL Schema and Database: PostgreSQL vs. YugabyteDB

Getting the total row counts of data in tables across various dimensions (per-table, per-schema, and in a given database) is a useful SQL technique to have in your toolkit. This blog post will guide you to obtain per-table row counts of all tables in PostgreSQL and YugabyteDB. This can serve as a first sanity check after migrating an application with pre-existing data from PostgreSQL to YugabyteDB.

This blog post also outlines how to get the following row counts broken down per table in a schema,

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TPC-C Benchmark: 10,000 Warehouses on YugabyteDB

July 28, 2020

By Karthik Ranganathan

Community News Databases Distributed SQL How It Works Open Source Performance Benchmarks YugabyteDB

TPC-C Benchmark: 10,000 Warehouses on YugabyteDB

We are excited to announce that the TPC-C benchmark implementation for YugabyteDB is now open source and ready to use! While this implementation is not officially ratified by the TPC organization, it closely follows the TPC-C v5.11.0 specification.

For those new to TPC-C, the aim of the benchmark is to test how a database performs when handling transactions generated by a real-world OLTP application. This blog post shows the results of running the TPC-C benchmark in addition to outlining our experience of developing and running a TPC-C benchmark against YugabyteDB.

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SQL Puzzle: Partial Versus Expression Indexes

June 18, 2020

By Karthik Ranganathan

Databases Distributed SQL PostgreSQL

SQL Puzzle: Partial Versus Expression Indexes

Here is an intriguing SQL puzzle we came across in the context of a real-world use case. This post shows the power of advanced RDBMS features such as partial indexes and expression indexes.

Let us assume we have a table in PostgreSQL named users, where each row in the table represents a user. The table is defined as follows.

CREATE TABLE users (
id SERIAL PRIMARY KEY,
email VARCHAR DEFAULT NULL,
name VARCHAR
);

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June 11, 2020

By Karthik Ranganathan

Community News Distributed SQL Open Source

100% Committed to Open Source, YugabyteDB Community Update – June 11, 2020

While it is still early days, it is exciting to see the YugabyteDB community hit some cool milestones! We wanted to share them with you, plus update you some additional community related news.

Our Commitment to Social Justice

First things first. Recent events that resulted in the death of George Floyd at the hands of police have been traumatic and painful for many of us, nationally and globally. It’s clear there is an overwhelming need for racial justice,

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Bringing Truth to Competitive Benchmark Claims – YugabyteDB vs CockroachDB, Part 2

May 4, 2020

By Karthik Ranganathan

CockroachDB Compare and contrast Distributed SQL Performance Benchmarks PostgreSQL

Bringing Truth to Competitive Benchmark Claims – YugabyteDB vs CockroachDB, Part 2

In part 1 of this blog series, we highlighted multiple factual errors in the Cockroach Labs analysis of YugabyteDB. In this second post we provide the next layer of detail behind YugabyteDB’s architecture, with an emphasis on comparing it to that of CockroachDB’s.

Contents of this post

TLDR
Query layer – reusing PostgreSQL
Storage layer – engineered for performance at scale
A deep dive into performance at large data sizes
Detailed YCSB results
Understanding performance in distributed SQL
- Large vs small data sets
- Range vs hash sharding
Conclusion

TLDR

Yugabyte SQL is based on a reuse of PostgreSQL’s native query layer.

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Bringing Truth to Competitive Benchmark Claims – YugabyteDB vs CockroachDB, Part 1

May 4, 2020

By Karthik Ranganathan

CockroachDB Compare and contrast Distributed SQL PostgreSQL

Bringing Truth to Competitive Benchmark Claims – YugabyteDB vs CockroachDB, Part 1

At Yugabyte, we welcome competition and criticism. We believe these aspects are essential to the wide adoption of a business-critical, fully open source project like YugabyteDB. Specifically, constructive criticism helps us improve the project for the benefit of our large community of users. Engineers at Cockroach Labs posted their analysis of how CockroachDB compares with YugabyteDB a few months ago. We thank them for taking the time to do so.

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5 Query Pushdowns for Distributed SQL and How They Differ from a Traditional RDBMS

March 4, 2020

By Karthik Ranganathan

Databases Distributed SQL

5 Query Pushdowns for Distributed SQL and How They Differ from a Traditional RDBMS

A pushdown is an optimization to improve the performance of a SQL query by moving its processing as close to the data as possible. Pushdowns can drastically reduce SQL statement processing time by filtering data before transferring it over the network, filtering data before loading it into memory, or pruning out entire files or blocks that do not need to be read. PostgreSQL is a highly optimized single-node RDBMS when it comes to pushdowns. Because Yugabyte’s YSQL API reuses the upper half of PostgreSQL,

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Achieving 10x Better Distributed SQL Performance in YugabyteDB 2.1

February 25, 2020

By Karthik Ranganathan

Databases Distributed SQL Open Source Performance Benchmarks PostgreSQL YugabyteDB

Achieving 10x Better Distributed SQL Performance in YugabyteDB 2.1

When starting the YugabyteDB project, our founding thesis was to build a high-performance distributed SQL database for the cloud native era. Achieving high performance will always remain an ongoing initiative, especially when additional optimizations are required to support new features and new use cases. We are excited that the current YugabyteDB 2.1 release has a number of improvements that make Yugabyte SQL’s performance 10x better on average than the previous 2.0 release (from September 2019).

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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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Blogs by: Karthik Ranganathan

Support for Geo-Partitioning and Enterprise-Grade Security Features

Our Commitment to Social Justice

Contents of this post

TLDR

Explore Distributed SQL and YugabyteDB in Depth