Databases

YugabyteDB Integrates with Arctype SQL Client

YugabyteDB Integrates with Arctype SQL Client

PostgreSQL has eaten the world. And so Yugabyte set out to build the most Postgres-compatible, scalable, and resilient database. YugabyteDB is not only wire compatible with PostgreSQL, it is code compatible by reusing the upper half of PostgreSQL. Thanks to this compatibility, YugabyteDB can connect to the vast majority of database tools that integrate with Postgres.

In a previous blog post, Yugabyte Developer Advocate Franck Pachot showed how to connect YugabyteDB in Arctype.

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YugabyteDB Savepoints: Checkpointing Work in Distributed Transactions

YugabyteDB Savepoints: Checkpointing Work in Distributed Transactions

Yugabyte brings best-in-class performance, scalability, and availability to YugabyteDB, a fully PostgreSQL-compatible SQL database. Because YugabyteDB’s architecture uses PostgreSQL at the SQL layer, we get a long-tail of PostgreSQL compatibility for free. But implementing savepoints requires deeper integration into YugabyteDB’s distributed persistence and transaction layers.

In this blog post, we’ll discuss why you should care about savepoints. We’ll also examine how we built savepoints into YugabyteDB’s distributed transaction layer,

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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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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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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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