This blog discusses the performance issues with wildcard lookups in YugabyteDB and showcases alternative methods to find specific data in a large dataset, including several varieties of phonetic matching and trigrams. A test plan is provided to demonstrate basic query timings.
Dimitri Farafonov, VP and Fellow Architect at Fiserv, recently sat down to discuss his role at this top global fintech and payments company. During the conversation, he discussed the priorities that guide Fiserv’s database selection process, along with the complexities involved in working to achieve low latency, data consistency, and massive bi-directional scalability, which are critical to Fiserv’s operations.
This blog provides a guide to building Spring Boot applications with YugabyteDB using GraalVM’s ahead-of-time (AOT) compilation to generate a native image. The guide covers the necessary prerequisites and steps to trigger the native build, including how to handle dependencies lacking reachability metadata with explicit runtime hints.
YugabyteDB receives globally recognized ISO 27001 certification, demonstrating the maturity of our security program and commitment to protecting customer data.
This blog covers the function and implementation compactions, focusing on those details and configurations that are relevant to YugabyteDB. The second half focuses on the behavior and prioritization of background compactions.
In storage systems based on LSM/MVCC, when a record is deleted, it’s not immediately removed. A delete marker (typically called a Tombstone) is placed on the record. As the number of tombstones increases, it could adversely affect the performance of a scan. In this blog, we are going to understand this problem and come up with solutions to address it.
In this blog post, we will explore the primary key differences between colocated and non-colocated databases/tables and then dive into the syntax implications of primary key usage on colocated and non-colocated tables/databases.
Backend developers working with databases often rely on query builders and object-relational mappings (ORMs) to facilitate database interactions. In this blog, we’ll investigate how the Knex.js query builder can be used to enhance the development experience with Node.js and YugabyteDB.
Accuracy and availability are important for any database management system. Learn about Yugabyte’s rigorous testing process for our core database product, straight from an insider who is involved every day.
There is now support for YugabyteDB in Testcontainers. This blog explores how to use Testcontainers to write integration tests for a Spring Boot application with the Yugabyte database.