Databases

With so many SQL tutorials available online, it’s easy to get confused about SQL server best practices. Start with the following five suggestions so you can add security to your server while optimizing its performance.

This blog post is part of a series on Cloudera’s Operational Database (OpDB) in CDP. Each post goes into more details about new features and capabilities. Start from the beginning of the series with, Operational Database in CDP. This blog post gives you an overview of the high availability configuration capabilities of Cloudera’s OpDB. Cloudera’s Operational Database (OpDB) is a cluster-based software, which comes configured for High Availability (HA) out of the box.

We built Kong to handle any API at any level of scale, but running APIs at scale means storing and managing data at scale. That’s why we’ve always recommended Apache Cassandra for the biggest Kong deployments. Cassandra is powerful and proven, but it does require some skill to install and operate – which is why we’re excited to hear that Datastax is making Cassandra easy to use at any level of scale with DataStax Astra, a Database-as-a-Service built on Apache Cassandra.

In today’s post, we’ll take a deep dive into Rails migrations. We’ll break down the migration into different pieces, and in the process, learn how to write an effective migration. We’ll learn how to write migrations for multiple databases, as well as how to handle failed migrations and techniques of performing rollbacks. To understand the whole post, you’ll need to have a basic understanding of databases and Rails.

This blog post is part of a series on Cloudera’s Operational Database (OpDB) in CDP. Each post goes into more details about new features and capabilities. Start from the beginning of the series with, Operational Database in CDP. Cloudera’s OpDB provides a rich set of capabilities to store and access data. In this blog post, we’ll look at the accessibility capabilities of OpDB and how you can make use of these capabilities to access your data.

Running real time data injection and multiple concurrent workloads on HBase clusters in production is always challenging. There are multiple factors that affect a cluster’s performance or health and dealing with them is not easy. Timely, up-to-date and detailed data is crucial to locating and fixing issues to maintain a cluster’s health and performance.