What database monitoring tooling is really costing your bottom line
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.
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The latest News and Information on Databases and related technologies.
pgvector for RAG: When you don't need a dedicated vector database
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.
The Data Race That Wasn't a Bug (and the One That Was)
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.
10 Best Database Monitoring Tools for 2026
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.
How savepoints quietly throttled our Postgres queue
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.
Load Test PostgreSQL Instantly using Production Recordings
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.
The Year-2 Price Cliff: What Your Observability Stack Really Costs Over 3 Years
I’m not the one whose phone lights up at 3 a.m. when production breaks. But I’ve spent years working alongside the engineers who are, and I’ve noticed that observability migrations happen for two reasons. Either engineering needed one, or, far more often, a quote landed that looked too good to refuse. The engineers rarely regret the first kind. The second kind they tell me about in year two, usually with a renewal notice in hand.
Devart Data Access Components add support for the latest IDEs and database platforms
The latest update to Devart Data Access Components is here, bringing support for RAD Studio 13 Florence Release 2, Lazarus 4.8, Microsoft SQL Server 2025, MySQL 9.7.x, and NexusDB 4.75.20. The release also introduces new security and authentication capabilities, along with improvements to transaction management, database connectivity, data handling, and performance.
Database change management on Databricks: migrations, environments, and AI-generated change
You wouldn’t ship untested SQL Server database changes – Why is Databricks different? Databricks is where the data estate is growing, and increasingly where AI workloads run and generate change. But schema change there still happens the hard way: views and stored procedures managed through manually versioned scripts, drift between workspaces discovered when a deployment fails, and no reliable record of what changed, when, where, or why. As AI raises the volume and speed of schema change, these gaps widen.
VictoriaTraces in VictoriaMetrics Cloud: Complete Observability is Here
Earlier this year, we launched VictoriaLogs in VictoriaMetrics Cloud, bringing fast and cost-effective log management to everyone. Today we launch the final major step toward full observability: VictoriaTraces is now available to all cloud users. With this release, you can now manage all three signals, metrics, logs, and traces, in one place with the predictable pricing, reliability, and the operational simplicity you’ve come to expect from VictoriaMetrics.