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New versions of SecureBridge, EntityDAC, and dbExpress drivers are out. All three now work with RAD Studio 13 Florence Release 2 and offer improved support for the Arm64EC target platform. Devart dbExpress drivers also add support for Microsoft SQL Server 2025 and MySQL 9.7, while SecureBridge gains SFTP upload resume, multipart/form-data support, and a new SSL/TLS demo.

G2's Fall 2026 Grid Report for Database Monitoring is out, and Redgate Monitor is named a Leader. G2 builds its reports from verified user reviews rather than paid placement, so this recognition comes from the people who use Redgate Monitor every day, and took time out of their lives to tell others what it's like. So, a big thank you to our customers, we're grateful for every review.

A slow query can affect an application before the database team knows what is causing it. A blocked session, failed job, or growing database file can create more problems if no one spots it early. That’s where SQL Server monitoring tools come in. They help you track database performance, find slow queries, monitor waits and locks, and see what changed before a problem occurred.

To monitor a database backup, make the backup script check its own output (exit code, file size, a table you know must be there) and ping a heartbeat URL only when all of it passed. If that ping does not arrive on schedule, you get an alert. A backup that failed, wrote an empty file, hung, or never started all look the same from the outside: no success ping.

Assessing the cost of a database monitoring tool isn't always straightforward. The quick reaction is to solely assess costs on a license-for-license basis.

Dedicated vector databases have become such a standard part of the RAG conversation that teams often add one before they have proved they need it. According to studies, over 70% of companies using LLMs are using vector databases and RAG to customize their models. That shows how quickly the pattern has become normal. However, it does not mean every RAG application needs a separate retrieval system. If your application already runs on PostgreSQL, pgvector may be enough.

Imagine this: you are testing the performance of some part of your application. Everything is going smoothly, the numbers look good, and as a last check you turn on Go’s race detector. Then, out of nowhere, it prints a warning you didn’t expect: So you look at it. You look at it again, and again, and you think: “What the…?” The race is between your code and a goroutine you never started, somewhere deep inside net/http. You have no idea how that is possible, or why.

If your company relies on multiple databases and applications, keeping track of database performance can become difficult. You may face challenges such as: As your database environment grows, identifying the cause of performance issues becomes harder without the right monitoring in place. I get why database monitoring tools have become an important part of managing database performance. They help you monitor database activity, spot performance issues, and find what is causing a slowdown.

At incident.io we are huge fans of Postgres; we've written about it a lot over the years, including how to choose the right indexes and how we're proud of being boring (The Pet Shop Boys). We use Postgres as our primary transactional database, which as of today has ~900 tables, and counting! The vast majority of our codebase does something along the following lines: read some data from Postgres, execute some business logic, then write that data back to Postgres. It is not, however, always that simple.

The first PostgreSQL post ran on a laptop: a demo app, a Docker container, and the proxymock CLI. That is the fastest way to see the idea. It is also not where your database problems live. Your real query mix lives in the cluster, where a Java service with a connection pool, an ORM and a schema migration tool sends the statements nobody wrote by hand. This post deploys an open source banking app to Kubernetes and records the queries one of its services sends to PostgreSQL.