Databases are often the biggest bottleneck when it comes to application performance. Over the years a number of new database designs have emerged to help with not only basic scalability and performance but also to help improve developer productivity and make building certain types of applications easier. That isn’t to say these new databases are magical — there are always trade-offs being made and certain things are sacrificed for gains in other areas.

PostgreSQL is a popular open source object-relational database system designed to work for a wide range of workloads from single machines to data warehouses to web services with many concurrent users. PostgreSQL runs on all major operating systems and is used by teams and organizations across the world, including Netdata. If you are using PostgreSQL in production, it is crucial that you monitor it for potential issues. And the more comprehensive the monitoring the better!

You are not the only one asking this seemingly popular question! Several companies are torn between the rise in appeal of open-source databases and the undeniable challenges inherent to their adoption. Let’s explore the trends, the drivers and the challenges related to open-source database adoption.

At the end of last year, we announced that Redgate’s database cloning technology was getting an upgrade: Multi-RDBMS, instance-level clones, and support for containerized workflows. This next generation of database provisioning provides DevOps test data to more teams for fast, quality releases across your software organization. Today, we invite you to join the early access program (EAP) for Redgate Clone.

Grafana Labs Mimir is a new time series database under AGPLv3-license. The engineering team did a great job by taking the best from Cortex TSDB, reducing its complexity and improving scalability in the same time. According to tests by Grafana Labs, Mimir can scale to a billion active time series and 50 million samples/s ingestion rate.

Similar, to the monitoring module in Icinga Web, Icinga DB Web also provides list views for hosts and services to provide the most common columns to reduce the backend query load.

In this DevOps 101 series, I introduce the concept of DevOps and talk about how you can include the database as a natural partner. In the previous post in the series, I discussed how automation introduces faster and more frequent deployments as a key benefit. We’re now going to take a deep dive into the value you can unlock through frequent deployments using database DevOps, along with how you get started doing them.

The best Redis® ever - version 7.0 - is now available on the Aiven platform.

Traditionally the Prometheus TSDB only accepts in-order samples that are less than one hour old, discarding everything else. Having this requirement has allowed Prometheus to be extremely efficient with how it stores samples. And in practice, it really hasn’t really been much of a limitation for users because of the pull-based model in Prometheus, which scrapes data at a regular cadence off of the targets being observed. Several use cases, however, need out-of-order support.

Aiven for Redis® Join us as we take a look at all of Redis's ins and outs.