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Category: Distributed SQL

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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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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Why We Built YugabyteDB by Reusing the PostgreSQL Query Layer

Why We Built YugabyteDB by Reusing the PostgreSQL Query Layer

Reusing PostgreSQL’s native query layer instead of writing a new PostgresQL-compatible query layer ground up has been one of the best design decisions we have made in YugabyteDB. As outlined in the challenges we faced building a distributed SQL database, we have battle scars to prove this insight – we started writing a PostgreSQL-compatible query layer from scratch before realizing that we simply cannot build the world’s best cloud native RDBMS in a timely manner if we persist down this path.

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Spanning the Globe without Google Spanner

Spanning the Globe without Google Spanner

Open Source Geo-Distributed Relational Database on Multi-Cluster Kubernetes

Google Spanner, conceived in 2007 for internal use in Google AdWords, has been rightly considered a marvel of modern software engineering. This is because it is the world’s first horizontally-scalable relational database that can be stretched not only across multiple nodes in a single data center but also across multiple geo-distributed data centers, without compromising ACID transactional guarantees.

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Bringing Distributed SQL to VMware Tanzu

Bringing Distributed SQL to VMware Tanzu

VMware Tanzu, the newest offering from VMware’s stable of proven enterprise products, brings together a portfolio of open source projects for modernizing applications and automating infrastructure management. VMware Tanzu provides a managed Kubernetes environment on VMware vSphere or any public cloud of choice that allows a consistent way to provision and deploy the code for application developers.

The Yugabyte team collaborated with VMware to certify YugabyteDB for Tanzu Kubernetes environments,

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YugabyteDB Engineering Update – April 13, 2020

YugabyteDB Engineering Update – April 13, 2020

We are excited to announce that YugabyteDB 2.1.3 is GA! You can read the official release notes here. This release shipped with over 60 new enhancements and fixes.

The Yugabyte team has been working from home in order to do our part with social distancing and to help with containment efforts. We have also transitioned to online meetings with our customers, partners, candidates, community, and fellow Yugabeings. We will continue with these and other measures until it’s determined to be safe otherwise.

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Scaling Relational Spring Microservices Without Load Balancers

Scaling Relational Spring Microservices Without Load Balancers

This article was originally posted on JAXenter.com.

Modern cloud native applications demand relational databases to be highly available while being able to scale to millions of requests (RPS) and thousands of transactions per second (TPS) on demand. This is becoming essential to meet the seamless experience demanded by business applications and their users. High availability and scalability in NoSQL databases like Apache Cassandra and MongoDB are well understood, but have been challenging problems to solve in relational databases.

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