The Distributed SQL Blog

My Yugabyte Journey into Distributed SQL Databases

My Yugabyte Journey into Distributed SQL Databases

This post was written by Nim Wijetunga, a Yugabyte intern during fall 2021. Nim’s currently a software engineering student at the University of Waterloo in Waterloo, Ontario, Canada.

My journey into distributed databases began in early 2021. I was an intern at Snowflake and was part of the core FoundationDB (FDB) team. FDB is an open source distributed key-value store. Snowflake and Apple are currently the largest contributors (and maintainers) of FDB.

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YugabyteDB Migration: What About Those 19 Oracle Features I Thought I Would Miss?

YugabyteDB Migration: What About Those 19 Oracle Features I Thought I Would Miss?

In 2019, I gave a presentation with the title, “19 features you will miss if you leave Oracle.” The talk focused on features used every day with Oracle—and those that may not be available in other databases. However, the goal of this presentation was not to influence any decision or outcome. 

Migrating from a commercial database is not about covering a full set of features. It’s a strategy to stay in control of the software that processes and stores enterprise data.

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Tutorial: How to Deploy Multi-Region YugabyteDB on GKE Using Multi-Cluster Services

Tutorial: How to Deploy Multi-Region YugabyteDB on GKE Using Multi-Cluster Services

The evolution of “build once, run anywhere” containers and Kubernetes—a cloud-agnostic, declarative-driven orchestration API—have made a scalable, self-service platform layer a reality. Even though it is not a one size fits all solution, a majority of business and technical challenges are being addressed. Kubernetes as the common denominator gives scalability, resiliency, and agility to internet-scale applications on various clouds in a predictable, consistent manner. But what good is application layer scalability if the data is still confined to a single vertically scalable server that can’t exceed a predefined limit?

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Tutorial: Getting Started with YugabyteDB and Docker

Tutorial: Getting Started with YugabyteDB and Docker

When developing modern applications, it is important to maintain dev/prod parity (that is, keep development, staging, and production as similar as possible). This should also extend to the local development environment.  However, containerization makes it easy to achieve consistency across all environments, even with more complicated components such as databases.

YugabyteDB is a cloud-native, distributed SQL database that is also PostgreSQL compatible. This interoperability makes it possible for developers to leverage existing tools,

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Multi-Cloud Distributed SQL: Avoiding Region Failure with YugabyteDB

Multi-Cloud Distributed SQL: Avoiding Region Failure with YugabyteDB

As Amazon CTO Werner Vogels often reminds us: ”Everything fails, all the time”. This means any component of the infrastructure will fail at some point. However, with more and more software being deployed in the cloud, today’s infrastructure must provide redundancy. In addition, the applications that sit on top of it must provide continuity over failures.

This involves database replication when the failure concerns data in motion. But there are different levels of failures and different protection technologies.

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Distributed SQL Tips and Tricks – December 16th, 2021

Distributed SQL Tips and Tricks – December 16th, 2021

Welcome back to our tips and tricks blog series! I have the distinct pleasure of recapping distributed SQL questions from around the Internet for the month of December.

This ongoing series would not be possible without Dorian Hoxha, Franck Pachot, and  Frits Hoogland. We also thank our incredible user community for their work with the technology.

Do you have any questions?

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How Kroger’s Data Architecture Powers Omnichannel Retail Experiences at Scale

How Kroger’s Data Architecture Powers Omnichannel Retail Experiences at Scale

At a recent Distributed SQL Summit, Sriram Samu, VP of Customer Technology at Kroger, discussed how his company’s data architecture unlocks digital and omnichannel experiences at scale. He provided a rare glimpse into how the business is bringing its data models into a new format. This format is easy to serve at speed, while still being able to integrate with legacy systems.

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Using GIN Indexes in YugabyteDB

Using GIN Indexes in YugabyteDB

At Yugabyte, we are committed to complete PostgreSQL compatibility. Similar to PostgreSQL, YugabyteDB supports the following three container column types. These three data types are extremely useful in various cases:

  • jsonb – Makes it useful for schema-less data use cases
  • tsvector – Supports full text search through a sorted list of distinct lexemes
  • array – Gives the flexibility to store a large composite variable-length value in a single field

Each data type’s utility is severely limited without an efficient way to index them.

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