Citus Data: Distributed PostGreSQL for Big Data with Ozgun Erdogan and Craig Kerstiens - Episode 13

Jan 8, 2018

Ozgun Erdogan and Craig Kerstiens from Citus Data discuss their work on scaling out PostGreSQL, including replication models, distributed backups, and upcoming features for real-time analytics. They also explore the considerations for deploying Citus and compare it to other offerings like Redshift and BigQuery.

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Introduction

00:00 • 2min

The Evolution of Postgres and the Birth of Citus

01:34 • 17min

Understanding Citus and its Replication Models

18:59 • 10min

Complexities of Backups in a Horizontally Scaled Database and a Recent Change for Fully-Consistent and Distributed Backups

28:39 • 2min

Considerations for Deploying Open Source Citus Data

30:52 • 10min

Upcoming Features and Improvements for SQL and Big Data Analytics

40:53 • 2min

Discussing SQL Scalability and the Need for Simplified Data Management

43:19 • 3min

Summary

PostGreSQL has become one of the most popular and widely used databases, and for good reason. The level of extensibility that it supports has allowed it to be used in virtually every environment. At Citus Data they have built an extension to support running it in a distributed fashion across large volumes of data with parallelized queries for improved performance. In this episode Ozgun Erdogan, the CTO of Citus, and Craig Kerstiens, Citus Product Manager, discuss how the company got started, the work that they are doing to scale out PostGreSQL, and how you can start using it in your environment.

Preamble

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Your host is Tobias Macey and today I’m interviewing Ozgun Erdogan and Craig Kerstiens about Citus, worry free PostGreSQL

Interview

Introduction
How did you get involved in the area of data management?
Can you describe what Citus is and how the project got started?
Why did you start with Postgres vs. building something from the ground up?
What was the reasoning behind converting Citus from a fork of PostGres to being an extension and releasing an open source version?
How well does Citus work with other Postgres extensions, such as PostGIS, PipelineDB, or Timescale?
How does Citus compare to options such as PostGres-XL or the Postgres compatible Aurora service from Amazon?
How does Citus operate under the covers to enable clustering and replication across multiple hosts?
What are the failure modes of Citus and how does it handle loss of nodes in the cluster?
For someone who is interested in migrating to Citus, what is involved in getting it deployed and moving the data out of an existing system?
How do the different options for leveraging Citus compare to each other and how do you determine which features to release or withhold in the open source version?
Are there any use cases that Citus enables which would be impractical to attempt in native Postgres?
What have been some of the most challenging aspects of building the Citus extension?
What are the situations where you would advise against using Citus?
What are some of the most interesting or impressive uses of Citus that you have seen?
What are some of the features that you have planned for future releases of Citus?

Contact Info

Citus Data
- citusdata.com
- @citusdata on Twitter
- citusdata on GitHub

Craig
- Email
- Website
- @craigkerstiens on Twitter

Ozgun
- Email
- ozgune on GitHub

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Links

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

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