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Retail Application Migration: Lessons Learned Moving from On-Prem to Cloud Native

Retail Application Migration: Lessons Learned Moving from On-Prem to Cloud Native

Recently, I came across a sample e-commerce application that demonstrates how to use Next.js, GraphQL engine, PostgreSQL, and a few other frameworks to build a modern web application. The application supports basic e-commerce capabilities such as product inventory and order management, recommendation system, and checkout function. This made me curious as to how much effort it would take to complete a retail application migration from an on-premise to cloud native solution. So I decided to try.

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Securing YugabyteDB: Part 2 – Client-to-Server Encryption in Transit

Securing YugabyteDB: Part 2 – Client-to-Server Encryption in Transit

In the first post in this series, we covered how to secure YugabyteDB’s internal RPC protocol using the TLS encryption protocol, also referred to as server-to-server encryption in transit. In this post, we secure the communication between SQL clients and the PostgresQL query interface of YugabyteDB, also called client-to-server encryption in transit. 

YugabyteDB—a 100% open source, distributed SQL database built to accelerate cloud native agility—stores important user and customer data at an organization.

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Performing Flexible IO Testing in YugabyteDB

Performing Flexible IO Testing in YugabyteDB

ybio is a PL/pgSQL based load generator for PostgreSQL and YSQL. This YugabyteDB-specific IO testing toolkit performs flexible IO testing to specific parts of the YugabyteDB infrastructure with no client installation. And because this toolkit is PL/pgSQL-based, it can also work on native PostgreSQL.

ybio is strongly inspired by Kevin Closson’s SLOB and pgio. Yugabyte Developer Advocate Franck Pachot took pgio and turned it into ybio.

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Announcing YugabyteDB 2.12: Seamless Security and Better Manageability

Announcing YugabyteDB 2.12: Seamless Security and Better Manageability

Last November, we announced the general availability of YugabyteDB 2.11, a major release which extends PostgreSQL compatibility of the open source distributed SQL database. All these features are readily available in this stable release for any production environment.

In addition to making these features GA, YugabyteDB 2.12 introduces several new capabilities and significant improvements towards seamless security and better manageability.

Seamless security

Building customer trust is a top priority at Yugabyte.

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PostgreSQL Timestamps and Timezones: How to Navigate the Interval Minefield

PostgreSQL Timestamps and Timezones: How to Navigate the Interval Minefield

In the second part of this blog series on PostgreSQL and YSQL date-time data types, the focus shifts to representing durations, or how long things last. Assuming the reader has read the first part and downloaded the companion code kit, this post explores the relevant data types, including interval, timestamp difference, and other related functions.

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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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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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