I recently attended a virtual event and heard the speaker comment, “Relational databases don’t scale.” To my ears, this is about as silly a statement as saying, “No one can eat 26 hot dogs in 12 minutes” right before Kobayashi shows up and eats 50. In my experience, relational databases scale when they’re placed in the hands of someone who knows what they’re doing. Just imagine if Kobayashi was your data architect!

Database DevOps has come of age. Now seen as a key technical practice which can contribute to the successful implementation of DevOps, it stops the database being a bottleneck and makes releases faster and easier. Conversely, perhaps, the automation and audit trails it introduces can help to protect personal data within databases and make compliance part of the same process rather than an additional time-consuming step outside it.

VictoriaMetrics is proud to announce that we consider vmbackup and vmbackupmanager to be feature-complete solutions as of release 1.85.3. These backup components are essential for ensuring the safety and integrity of your data, and we have made a number of improvements in recent releases to make them even more reliable and user-friendly.

If you are working with large amounts of data that will primarily be used for analytics, a column database might be a good option. There are a lot of different options when it comes to choosing a database for your application. A common discussion seems to be the high-level SQL vs. NoSQL database argument of whether data should be stored in a relational database or in a NoSQL alternative like key-value, document or graph databases.

As technology improves and customer demands change, many companies must provide fast, engaging, and secure services. Developers rely on platforms that support sub-millisecond response times to power these capabilities in their applications. Amazon ElastiCache and Redis are two of the most popular platforms for building fast, highly available, and scalable data stores.

As a data professional, I often think about all the things around me generating data and consider where this data is ultimately being used. Have you ever taken a minute to consider exactly how much data is being generated at any point in time? I love collecting data and looking at ways it can be used and living in a “smart” home with appliances logging and reporting usage patterns certainly provides a lot of opportunities.

At LogicMonitor, ingesting and processing time series metric data is arguably the most critical portion of our unified observability platform. In order to fully prepare for growth, scale, and fault-tolerance, we have evolved what we refer to as our Metrics Processing Pipeline from a monolith to a microservice-driven architecture.

MongoDB has evolved into the database solution of choice for developers looking to build efficient, scalable applications in the cloud. But, as when using any cloud-based infrastructure, using MongoDB introduces an additional layer of complexity to customers’ IT spend. This week, we announced support for MongoDB on the CloudZero Platform.