Ecosystem Integrations

YugabyteDB and Red Hat OpenShift: Resilient Kubernetes Workloads at Scale

YugabyteDB and Red Hat OpenShift: Resilient Kubernetes Workloads at Scale

Kubernetes has become widely adopted in the Fortune 500. Many companies are now using the platform to run stateless and stateful applications on-premises or as hybrid cloud deployments in production. Of course, with any new technology, there are growing pains when running resilient Kubernetes workloads. But most executives and developers agree that the benefits far outweigh the challenges.

Data on the Kubernetes ecosystem is evolving rapidly with the rise of stateful applications. However,

Read more

Log Aggregation in YugabyteDB with Grafana Loki

Log Aggregation in YugabyteDB with Grafana Loki

Log aggregation is an integral part of a distributed system. As the name suggests, a distributed system will have multiple processes across multiple machines, and each process will generate a lot of data. Looking at the data in silos is time-consuming and wouldn’t yield important information as the data sets still need to be correlated. But aggregating the logs is a huge productivity booster that helps to transform the raw log data into insightful information.

Read more

Building a Simple Application with YugabyteDB and Prisma

Building a Simple Application with YugabyteDB and Prisma

When building modern web applications, developers often find data modeling and data access to be productivity bottlenecks. Rather than moving towards a schema-less database solution, many find using an ORM (object-relational mapping) tool with SQL to be their preferred option. The Node.js community has long been supportive of the Sequelize ORM, with Prisma being a newer option for those looking to model, migrate, and query their data.

In this blog, we’ll get acquainted with Prisma and how it interfaces with Node.js and YugabyteDB.

Read more

Change Data Capture (CDC) Using a Spring Data Processing Pipeline

Change Data Capture (CDC) Using a Spring Data Processing Pipeline

Change Data Capture (CDC) is a technique to capture changes in a source database system in real-time. The goal is to stream those changes as events through a data processing pipeline for further processing.

CDC enables many use cases, especially in modern microservices-based architecture that involves a lot of bounded services. It is the de-facto choice for use cases such as search indexes, in-memory data cache, real-time notifications, data sync between sources,

Read more

Explore Distributed SQL and YugabyteDB in Depth

Discover the future of data management.
Learn at Yugabyte University
Get Started Business
Browse Yugabyte Docs
Explore docs Business
PostgreSQL For Cloud Native World
Read for Free Business