Operations | Monitoring | ITSM | DevOps | Cloud

Database Administrators (DBAs) rely on time series data every day, even if they don’t think of time series data as a unique data type. They rely on metrics such as CPU usage, memory utilization, and query response times to monitor and optimize databases. These metrics inherently have a time component, making them time series data. However, traditional databases aren’t specifically designed to handle the unique characteristics and workloads associated with time series data.

We recently launched the State of the Database Landscape 2024 survey results, with information from almost 4,000 database professionals from around the globe. A clear picture emerged from the results, suggesting that 2024 is the year that skill diversification among database professionals is imperative. There’s the need to manage multiple databases, to migrate to the cloud, to introduce continuous delivery with DevOps, and even incorporating Generative AI into the mix.

Azure Cosmos DB, a global, multi-model database by Microsoft Azure, ensures globally responsive and scalable applications with low-latency, high-throughput data access. With support for diverse data models, global distribution, flexible consistency models, automatic scaling, and comprehensive SLAs, it’s crucial for modern applications requiring agility, security, and compliance.

A large proportion of our customers rely on eG Enterprise to monitor and troubleshoot application and end-user experience problems caused by problems in underlying database dependencies. Our end-to-end unified monitoring and root-cause analysis platform supports all major database technologies. Over recent years, we have witnessed a significant shift from traditional on-premises databases to more dynamic, scalable solutions.

Monitoring Redis instances is essential for maintaining performance, reliability, and security. It allows you to detect issues early, optimize resources, and provide a seamless experience for both developers and end-users. Monitoring your database allows you to track key performance metrics such as memory usage, CPU usage, and query response times. By analyzing these metrics, you can identify performance bottlenecks, optimize queries, and ensure that Redis is operating efficiently.

Datadog Database Monitoring (DBM), which provides host-level and query performance metrics and insights for PostgreSQL, MySQL, and SQL Server, is now available for Oracle. Oracle is one of the most common database types, and now teams that operate Oracle databases can use Datadog to monitor these resources alongside telemetry from across their environments.