VoltDB is an ACID-compliant, in-memory relational database designed to support real-time analytics. VoltDB’s in-memory storage, stored procedures, and shared-nothing architecture make it specifically optimized for quickly processing massive streams of data. This means VoltDB is tailored for use cases like online gaming, telecommunication, and financial applications, which require fast data processing.

This article explains how to monitor service process on your service with Bleemeo using MySQL as an example. This feature is what we called "Key Process Monitoring" and is described by our documentation. Currently, you can monitor any service process automatically discovered by Bleemeo. All metrics are detailed in our documentation, in a few words, metrics related to memory, cpu, network and i/o used by this process are gathered by the agent.

Regardless of the tech stack used, many developers have already used Redis or, at least, heard of it. Redis is specifically known for providing distributed caching mechanisms for cluster-based applications. While this is true, it’s not its only purpose. Redis is a powerful and versatile in-memory database. Powerful because it is incredibly super fast. Versatile because it can handle caching, database-like features, session management, real-time analytics, event streaming, etc.

SQL is great, but sometimes you may need something else. By and large, the prevalent type of data that data engineers deal with on a regular basis is relational. Tables in a data warehouse, transactional data in Online Transactional Processing (OLTP) databases — they can all be queried and accessed using SQL. But does it mean that NoSQL is irrelevant for data engineering?