Introducing HighPerf, our highly scalable raw storage database that facilitates smarter analytics, faster troubleshooting, and better bandwidth management.

Welcome to our latest benchmark figures for Aiven for PostgreSQL on AWS, GCP and MS Azure.

To make life easier for database admins and simplify DevOps, Aiven now offers a Kubernetes Operator for Aiven for PostgreSQL and Aiven for Apache Kafka services. Find out how you can use it to manage your whole service stack.

Application developers have a choice between two main categories of database: SQL (Structured Query Language) and NoSQL (Not Only SQL). SQL databases, also known as relational databases, have been in use for over 40 years. Despite their age, SQL databases remain extremely popular with developers. Of the top 10 results on DB-Engines’ list of most popular database management systems in September 2021, six were relational, or SQL-based.

SQL Server monitoring is continuous collection and analysis of usage, performance, and event metrics for Microsoft SQL Server. It’s the first step in optimizing performance for applications that depend on your data platform. Highly effective monitoring gives a bird’s-eye view of your entire data estate. It also provides the deep analytics necessary to perform root cause analysis on the most challenging performance problems.

You may have read or heard about IDC’s recent Global DataSphere Forecast, 2021-2025, which predicts that global data creation and replication will experience a compound annual growth rate (CAGR) of 23% over the forecast period, leaping to 181 zettabytes in 2025. That’s up from 64.2 zettabytes of data in 2020 which, in turn, is a tenfold increase from the 6.5 zettabytes in 2012.

Managing any database ecosystem is difficult enough: taking backups, maintaining statistics, and doing performance tuning all tax the time of the DBA or database developer. The job is complex even without considering the work you do to manage the various schema and data drifts that can occur. Unless you operate in a vacuum or within a single person organization (and even then, schema drift can occur), drift is going to manifest naturally and as the size of the environment expands.

When drift happens within a database, it can occur at a couple of different levels. Drift refers to entities—tables, views, or even data—out of synchronization with each other. This could be a difference in schema structure, data, or even operational metadata like permissions. Often, drifts happen between two different environments like development and staging databases.

Investigating your family tree can be an interesting experience. For example, what if you discovered you were related to a famous person who won a Nobel Prize or performed a heroic act? Conversely, what if you realized you had an ancestor who was an infamous criminal? Much like examining your genealogy can be an exciting adventure, looking at the family tree of your database can prove to be just as rewarding. Databases occasionally undergo a phenomenon known as drift.

The knapsack problem: how to use limited luggage space to pack only and all the items you're most likely to need? Enter PostgreSQL! Come and find out how to use the world's best open source database to help you pack.