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The latest News and Information on Databases and related technologies.

Tempo 3.0 release: a new architecture for scale and lower TCO, TraceQL metrics GA, and more

Tempo started with a simple goal: make distributed tracing easier to run at scale. As tracing adoption has grown, however, so have the challenges, including higher data volumes, more complex architectures, and increasing demand for real-time insights directly from traces. Over the last year, we’ve been evolving Tempo’s architecture to meet that moment. And today, we’re sharing the results of those efforts with the release of Tempo 3.0.

What's New in Tempo 3.0

Tempo 3.0 introduces a major architectural shift that decouples the read and write paths, with Kafka handling durability on the write side and a new live store serving recent traces on the read side. Blocks are now written at a replication factor of one instead of three, significantly reducing storage overhead. This release also brings TraceQL metrics to general availability, adds comparison operators for filtering metric results at query time, and introduces a new Tempo CLI redact command for removing sensitive trace data on demand without waiting for retention to expire.

Test Data Management Demo | Compliance without Compromise

Compliance Without Compromise: Test Data Management That Finally Fits You know you shouldn't have sensitive production data in test environments. But every time you look at fixing it, the options feel impossible: enterprise tools that cost six figures and take months to implement, or DIY scripts that sort of work until they don't. So, it stays on the backlog.

BigQuery CI/CD and Database DevOps with Harness | Harness Blog

Modern data platforms are evolving rapidly, and Google Cloud BigQuery has become a core part of analytics, AI, and large-scale reporting architectures. Teams (including Harness) rely on BigQuery to process and analyze massive datasets, but managing schema changes in a secure, repeatable way can still be challenging.

The options within Test Data Management - Enterprise, DIY or Redgate

Compliance Without Compromise: Test Data Management That Finally Fits You know you shouldn't have sensitive production data in test environments. But every time you look at fixing it, the options feel impossible: enterprise tools that cost six figures and take months to implement, or DIY scripts that sort of work until they don't. So, it stays on the backlog.

The Compliance Gap in Test Data Management

Compliance Without Compromise: Test Data Management That Finally Fits You know you shouldn't have sensitive production data in test environments. But every time you look at fixing it, the options feel impossible: enterprise tools that cost six figures and take months to implement, or DIY scripts that sort of work until they don't. So, it stays on the backlog.

Safe Database Change at Scale with Flyway Enterprise | The Tony and Tonie show Ep45

AI-assisted coding may speed up delivery, but it can also increase the risk around database changes. Here’s how Flyway helps teams stay in control. Tony and Tonie discuss how Flyway Enterprise helps teams build control into the database change process: immediate change visibility, continuous risk reduction, and secure, traceable deployment from commit to production.

The importance of taking the initiative (a chat with Chris Yates) | The Simple Talk Podcast

Taking the initiative. Prioritizing relationships. Doing the work nobody else wants to do. These are just some of the elements that contributed to Chris Yates’ rise from a developer to a DBA and, eventually, a Senior Vice President. As he explains to Steve Jones, “you are the CEO of your own brand.” Also in the episode: discover Chris’ thoughts on AI, the importance of community, and the one thing he’d now do differently if he were to start from scratch.

Monitor Azure Managed Redis with Datadog

Azure Managed Redis is Microsoft’s fully managed, enterprise-tier in-memory data store. It is designed for the low-latency caching, session storage, and real-time data needs of modern applications, including AI workloads that depend on fast vector and embedding lookups. Because user-facing applications often query Redis directly, even small regressions in latency, hit rate, or memory pressure can degrade the user experience.

DuckDB: Not Quack Science | Ubuntu Summit 26.04

Could you process hundreds of gigabytes of data on your laptop, or tens of terabytes on a single server? DuckDB is an open source SQL database system, geared towards analytical workloads. DuckDB ships a state-of-the-art database architecture as a single package, that is available both as a command line tool and as an in-process library. Uniquely among databases, DuckDB focuses on user experience and portability, making it easy to set up almost anywhere.