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Author: Karthik Ranganathan

TPC-C Benchmark: 10,000 Warehouses on 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

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

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

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

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

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

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

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

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

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 Plume Handled Billions of Operations Per Day Despite an AWS Zone Outage

How Plume Handled Billions of Operations Per Day Despite an AWS Zone Outage

Enterprises deploy YugabyteDB clusters across multiple availability zones (AZs) in order to ensure continuous availability of their business-critical services even when faced with cloud infrastructure failures like zone outages. On November 12, 2019, there was one such outage of an entire availability zone in the eu-central-1 region of AWS. This was reported on the AWS status page on that day, along with an official update.

In this post, we are going to look at how a Yugabyte Platform customer,

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How YugabyteDB Scales to More than 1 Million Inserts Per Sec

How YugabyteDB Scales to More than 1 Million Inserts Per Sec

There are a number of well-known experiments where eventually-consistent NoSQL databases were scaled out to perform millions of inserts and queries. Here, we do the same using YSQL, YugabyteDB’s PostgreSQL-compatible, strongly-consistent, distributed SQL API. We created a 100-node YugabyteDB cluster, ran single-row INSERT and SELECT workloads with high concurrency – each for an hour and measured the sustained performance (throughput and latency). This post details the results of this experiment as well as highlights the key aspects of the YugabyteDB architecture that makes it fit for such high-volume ingest workloads.

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