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The latest News and Information on Databases and related technologies.

ADO.NET SQL Connection Providers for SQL Server Compared

Selecting an ADO.NET provider may seem like a simple, one-time decision, but it can affect performance, compatibility, and long-term maintainability for years. The provider sits between your application and SQL Server and affects everything from connection management and authentication to support for new database features. Also, today, SQL Server 2025 delivers new cloud-optimized features and modern security and System.Data.SqlClient has become legacy software.

Detecting Data Masking Gaps in a CI Pipeline | The Tony and Tonie show Ep46

Your schema changed. Did your masking rules keep up? Here’s how Flyway and Test Data Manager can catch gaps and prevent PII exposure in dev and test. Tony and Tonie discuss how Flyway and Redgate Test Data Manager can work together in a CI pipeline to detect schema changes that introduce unmasked sensitive columns, helping teams keep production-derived test data protected as the database evolves.

Migrate to Azure Managed Redis with Datadog and Eden

Azure Managed Redis is a Microsoft first-party, fully managed in-memory data store, replacing Azure Cache for Redis tiers. It includes Redis Enterprise features such as RediSearch for vector search and full-text search, in addition to RedisJSON, RedisTimeSeries, and Active Geo-Replication. As Azure Cache for Redis reaches end of life, more teams are planning migrations to Azure Managed Redis in search of better performance, lower cost, and modern capabilities for AI and real-time workloads.

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.