The Distributed SQL Blog

What’s New and Improved in YugabyteDB Docs – September 2020

What’s New and Improved in YugabyteDB Docs – September 2020

Welcome to this month’s edition of what’s new and improved in YugabyteDB Docs. We’re continually adding to and updating the documentation to give you the information you need to make the most out of YugabyteDB. This post covers recent content added, and changes made, to the YugabyteDB documentation since the last posting.

YSQL

What is YSQL? Yugabyte Structured Query Language (YSQL) is a fully-relational, PostgreSQL-compatible API.

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Heroku Add-on for Yugabyte Cloud Now Available in Public Beta

Heroku Add-on for Yugabyte Cloud Now Available in Public Beta

Today, we are pleased to announce the public beta release of the Heroku Yugabyte Cloud add-on. With new accessibility to the Heroku marketplace, the process of deploying a fully-managed distributed SQL database in the cloud is now radically simple. For those of you who are new to distributed SQL, YugabyteDB is a Google Spanner-inspired, cloud native distributed SQL database that is 100% open source. It puts a premium on high performance, data resilience, and geographic distribution,

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Distributed SQL Tips and Tricks for PostgreSQL and Oracle DBAs – Sep 9, 2020

Distributed SQL Tips and Tricks for PostgreSQL and Oracle DBAs – Sep 9, 2020

Welcome to this week’s tips and tricks blog where we explore both beginner and advanced YugabyteDB topics for PostgreSQL and Oracle DBAs.

Please note that most examples in the post make use of the Northwind sample database. Instructions on how to get it installed are here.

Ok, let’s dive in…

Is there a functional equivalent to Oracle’s NVL in PostgreSQL or YugabyteDB?

In a nutshell,

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Recap: YugabyteDB at KubeCon + CloudNativeCon Europe 2020

Recap: YugabyteDB at KubeCon + CloudNativeCon Europe 2020

What a great KubeCon + CloudNativeCon Europe 2020 earlier this month! We were happy to participate, sponsor, and help #KeepCloudNativeConnected.

Thank you to everyone who stopped by the YugabyteDB booth, and a big thanks to all who redeemed your virtual swag of $5 to charity. Together, your swag redemptions ended up in more than $3,000 being donated across these three charities:

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Row Counts of Tables in a SQL Schema and Database:  PostgreSQL vs. 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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Using Envoy Proxy’s PostgreSQL & TCP Filters to Collect Yugabyte SQL Statistics

Using Envoy Proxy’s PostgreSQL & TCP Filters to Collect Yugabyte SQL Statistics

Layer 7 proxies like NGINX and HAProxy have been popular since the mid-2000s. The term “proxy” refers to their role as an intermediary for the traffic between an application client and an application server. The “layer 7” classification comes from the fact that these proxies take routing decisions based on URLs, IPs, TCP/UDP ports, cookies, or any information present in messages sent over a layer 7 (aka application layer) networking protocol like HTTP and gRPC.

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Webinar Recap: CRUD Operations with Hasura GraphQL and Distributed SQL

Webinar Recap: CRUD Operations with Hasura GraphQL and Distributed SQL

For those of you who missed last week’s YugabyteDB Community Q&A session, which covered GraphQL fundamentals, here’s the playback:

If you are interested in further exploring the possibilities of Hasura GraphQL and Distributed SQL, check out these resources.

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Getting Started with Hasura GraphQL Remote JOINs on Multi-Cloud Distributed SQL

Getting Started with Hasura GraphQL Remote JOINs on Multi-Cloud Distributed SQL

Remote joins in Hasura GraphQL extend the concept of joining data across tables, to being able to join data across tables and remote data sources. In this blog post we are going to demonstrate this capability by configuring the following set up.

  • A 3 node YugabyteDB cluster running on GKE with a Hasura GraphQL Engine attached
  • A 3 node YugabyteDB cluster running on AKS with a Hasura GraphQL Engine attached
  • A Remote Schema and Remote Relationship configured
  • The ability to issue GraphQL queries that join data from two different databases,

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Deploying a Real-Time Location App with Hasura GraphQL Engine and Distributed SQL

Deploying a Real-Time Location App with Hasura GraphQL Engine and Distributed SQL

Hasura is one of the leading vendors in the GraphQL ecosystem. They offer an open source engine that connects to your databases and microservices, and then auto-generates a production-ready GraphQL backend. GraphQL is a query language (more specifically a specification) for your API, and a server-side runtime for executing queries by using a type system you define for your data. GraphQL is often used for microservices, mobile apps, and as an alternative to REST.

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Run the REST Version of Spring PetClinic with Angular and Distributed SQL on GKE

Run the REST Version of Spring PetClinic with Angular and Distributed SQL on GKE

Java developers know that Spring Data makes it easy to use data access technologies, relational and non-relational databases, map-reduce frameworks, and cloud-based data services. When YugabyteDB is combined with Spring, Java developers are able to leverage their familiarity with PostgreSQL while gaining the added benefits of distributed SQL. These “out-of-the-box” benefits include geo-data distribution, high performance, and horizontal scalability, which are impossible or difficult to achieve with monolithic SQL databases.

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