IBM DB2 is a database management system that runs on a wide range of technologies, including Linux, UNIX, Windows, mainframes, and IBM Power Systems. You can use DB2 as a managed service in the cloud or deploy it in a cluster to provide high availability, making it suitable for a wide range of enterprise and customer-facing applications.

Unlike traditional SQL databases, NoSQL databases, or “non-SQL” databases, do not store their data in tabular relations. Originally designed for modern web-scale databases, they have found widespread use in present-day big data and real-time web applications. Some of the most commonly used data structures include key-value, wide column, graph, and document stores.

Database security refers to the various measures organizations take to ensure their databases are protected from internal and external threats. Database security includes protecting the database itself, the data it contains, its database management system, and the various applications that access it. Organizations must secure databases from deliberate attacks such as cyber security threats, as well as the misuse of data and databases from those who can access them.

Last week I rolled out a simple patch that decimated the response time of a Postgres query crucial to Checkly. It quite literally went from an average of ~100ms with peaks to 1 second to a steady 1ms to 10ms. However, that patch was just the last step of a longer journey. This post details those steps and all the stuff I learned along the way. We'll look at how I analyzed performance issues, tested fixes and how simple Postgres optimizations can have spectacular results.

Let’s not bury the lede here: we use Observability-Driven Development at Honeycomb to identify and prevent DB load issues. Like every online service, we experience this familiar cycle. This is not a bad thing! It’s a normal thing. Databases are easy to start with and do an excellent job of holding important data.

MongoDB Atlas is a fully managed NoSQL database that deploys onto the cloud platform of your choice: AWS, Azure, or GCP. Atlas provides built-in security features and automatically distributes clusters across availability zones to help ensure high availability and uptime. We’re excited to announce that with our new integration, you can now monitor MongoDB Atlas health and performance metrics alongside the rest of your cloud infrastructure and the applications that depend on your database.

Oracle database availability and performance is key. Gain insight into what happens within your Oracle environment. Using the NiCE Oracle Management Pack for Microsoft SCOM, advanced monitoring has never been easier. The NiCE Oracle Management Pack smart algorithm determines problems and their severity way upfront. Leverage your existing investment, reduce costs, save time and build efficiencies that will last beyond your expectations.

Amazon DynamoDB is a key-value and document database that allows you to easily scale to huge numbers of records with single digit millisecond performance. However, since it’s a managed service, you have less visibility with traditional monitoring tools. As such, it becomes even more important to take advantage of the available monitoring tools in AWS. In this post, we’ll explain how to use CloudWatch to monitor DynamoDB and what is important to watch.

Amazon DocumentDB is an AWS-managed document database service that supports MongoDB, the well known open source database. As a managed service, AWS automatically handles database management tasks, autoscales database clusters, and backs up your data to S3. DocumentDB implements the Apache 2.0 open source MongoDB 3.6 API, making it easy to migrate your existing MongoDB workloads to DocumentDB.