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Category: PostgreSQL

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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Follow-up: Evaluating CockroachDB vs YugabyteDB Webinar

Follow-up: Evaluating CockroachDB vs YugabyteDB Webinar

Earlier this week, Yugabyte CTO Karthik Ranganathan presented the live webinar: Evaluating CockroachDB vs YugabyteDB, with a spotlight on comparing PostgreSQL features, architecture, and the latest performance benchmarks between the two databases. We were delighted to see such interest in the topic, dive deeper into some of the topics we raised in parts 1 and parts 2 of the blog series, Bringing Truth to Competitive Benchmark Claims – YugabyteDB vs CockroachDB, and answer questions from the audience.

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Part 2: Airflow DAGs for Migrating PostgreSQL Data to Distributed SQL

Part 2: Airflow DAGs for Migrating PostgreSQL Data to Distributed SQL

Welcome to part two of our series on how to integrate Apache Airflow and YugabyeDB. In part one we showed you how to get Airflow configured to use YuagbyteDB as a backend. In this second post we’ll show you how to build an Airflow workflow that will migrate data between PostgreSQL and YugabyteDB.

What’s YugabyteDB? It is an open source, high-performance distributed SQL database built on a scalable and fault-tolerant design inspired by Google Spanner.

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Part 1: Deploying a Distributed SQL Backend for Apache Airflow on Google Cloud

Part 1: Deploying a Distributed SQL Backend for Apache Airflow on Google Cloud

Apache Airflow is a popular platform for programmatically authoring, scheduling, and monitoring workflows. Airflow has been deployed by companies like Adobe, Airbnb, Etsy, Instacart, and Square. The advantage of defining workflows as code is that they become more maintainable, versionable, testable, and collaborative. Airflow is used to author these workflows as directed acyclic graphs (DAGs) of tasks. Airflow’s scheduler executes your tasks on an array of workers while following the specified dependencies.

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Follow-up: Postgres Conference Webinar – Introduction to YugabyteDB

Follow-up: Postgres Conference Webinar – Introduction to YugabyteDB

I delivered the webinar “YugabyteDB: a distributed PostgreSQL database” last week. It was hosted by Postgres Conference in a series that they’d arranged so that the speakers who’d been selected to speak at their big annual conference in New York City in March could reach their audience. COVID-19 brought that event’s cancellation. This brief post tells you where you can find the edited videorecording and the PDF version of the slides that I used. It also gives me the chance to answer the couple of questions from attendees that shortness of time prevented me from answering during the webinar.

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Oracle vs PostgreSQL: First Glance – Testing YugabyteDB’s Compatibility

Oracle vs PostgreSQL: First Glance – Testing YugabyteDB’s Compatibility

Roland Takacs wrote an interesting blog post titled Oracle vs PostgreSQL: First Glance earlier this month. The genesis for his blog post was that he was in the middle of migrating his current Oracle tech stack to Python, parquet files, and PostgreSQL. As such, Roland thought it might be a good exercise to document the various Oracle features he was accustomed to and figure out what the equivalent functionality was in PostgreSQL. In his post,

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Boosting Performance for Small Distributed SQL Data Sets with Colocated Tables

Boosting Performance for Small Distributed SQL Data Sets with Colocated Tables

Editor’s note – This post was updated July 2020 with new release information

An Introduction to Colocated Tables

In YugabyteDB v2.1, we released a new feature in beta: colocated tables. And we were excited to announce the general availability of colocated tables, along with many other exciting new features, in YugabyteDB 2.2. In this post, we’ll explain what colocated tables are in a distributed SQL database,

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Distributed SQL Tips and Tricks – May 8, 2020

Distributed SQL Tips and Tricks – May 8, 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:

How can I connect YugabyteDB with Apache Spark?

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INSERT INTO Yugabyte (We’re Hiring, May 2020)

INSERT INTO Yugabyte (We’re Hiring, May 2020)

Recent Yugabyte Highlights and Happenings

The strong momentum continues here at Yugabyte! This week we set the record straight regarding some misconceptions published by a competitor. We also released YugabyteDB v2.1.5, and now have more than 1000 members in the YugabyteDB community Slack channel! Never a dull moment in distributed SQL!

Last month, we held the first virtual Silicon Valley PostgreSQL Meetup,

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YugabyteDB Engineering Update – May 6, 2020

YugabyteDB Engineering Update – May 6, 2020

YugabyteDB Release Updates

We are excited to announce that YugabyteDB 2.1.5 is GA! The 2.1.5 release shipped with over 40 new enhancements and fixes. Also, yesterday we hit a milestone that we are very proud of–we welcomed our 1000th member to the YugabyteDB community Slack channel! Congrats to Rob Sami for being the 1000th member, and thank you to the entire YugabyteDB community for your contributions and support along the way.

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