Handling Automatic ID Generation in PostgreSQL with Node.js and Sequelize
There are many ways to handle ID generation in PostgreSQL. In this blog, we’ll demonstrate four ways to do so in Sequelize for PostgreSQL and YugabyteDB.
There are many ways to handle ID generation in PostgreSQL. In this blog, we’ll demonstrate four ways to do so in Sequelize for PostgreSQL and YugabyteDB.
Let’s see how to capture pg_stat_statements from all the nodes in a persistent table to use for analysis. The data can then be stored in YugabyteDB tables, accessible from any node unless purged. Want to see how it can be done?
Every SQL execution in PostgreSQL and therefore in YugabyteDB YSQL takes time to process. A common way to identify how much is time spent on processing is to use the pg_stat_statements view in the database. However, the time visible in pg_stat_statements might differ from the time a database client registers for the execution. Where does this difference come from? Let’s take a look.
Learn how to best use Query Planner hints in the YugabyteDB database to optimize business queries based on how applications expose them. Walk through a use case that utilizes data sets from two popular TV shows to find total viewership per season, episode, etc.
This blog explores how to import and export Avro (a row-based storage format file) and Parquet (a columnar storage format file) and how to process the data with a YugabyteDB database using Azure Databricks.
Finding one-to-one mapping of the differences between monolithic and cloud-native databases is difficult.
In this blog, we compare YugabyteDB and Oracle (RAC, Data Guard) via availability objectives.
This should help you understand how Oracle MAA options map to YugabyteDB’s intrinsic features when considering migration projects.
In this blog, we explore how to transfer and process data from YugabyteDB (YBDB) to Azure Blob Storage or Azure Data Lake Storage using Azure EventHub through YBDB’s Change Data Capture (CDC) feature.
Our team continues to deliver new innovations, so we are excited to announce our latest stable release—YugabyteDB 2.14, which delivers higher performance, security and YugabyteDB Anywhere enhancements.
YugabyteDB is quickly becoming the cloud native relational database for the world’s most demanding enterprises, driving data-driven innovation in the face of growth, uncertainty, and change.
Hello. I’m Sahith, a Yugabyte engineering intern. I’m a 2022 Computer Science Engineer graduate from PES University in Bangalore who loves to solve problems with code. I also recently decided to join Yugabyte in a full-time engineering role. And lucky for me, this turned out to be one of the best decisions I’ve made.
However, before joining the company full time, I wanted to share some takeaways from my internship experience.
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In Java development, garbage collection is a routine task. Applications generate garbage all the time. And that garbage is meticulously cleaned out by CMS, G1, Azul C4 and other types of collectors. Basically, our applications are born to bring value to this world, but nothing is perfect—including our applications that leave litter in the Java heap.
However, the story doesn’t end with the Java heap. In fact, it only starts there. Let’s take the example of a basic Java application that uses a relational database—such as PostgreSQL—and solid state drives (SSDs) as a storage device.
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