Operations | Monitoring | ITSM | DevOps | Cloud

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.

Before we start, please take a moment to appreciate what day it is. IoT, or Internet of Things, has been a buzzword for longer than usual. Buzzwords usually have two common properties, and then their paths fork. I like thinking about buzzwords and about the useful aspects of what they mean. The most recent public example focuses on another buzzword currently in its hype phase: observability.

LogicMonitor dashboards are truly customizable — customizable enough to allow users to visualize virtually anything. Dashboards provide our users with a wide array of capabilities, from capacity planning and service availability notifications to root cause analysis and IT spend forecasting capabilities. We’ve seen LogicMonitor users get radically innovative when it comes to creating unique dashboards that add value to their lives both in and outside of work.

Datadog was founded in 2010 by Olivier Pomel and Alexis Le-Quoc. They develop the Datadog to reduce the friction they experienced between system administration teams and developers. Together they raised over $648 million to bring its valuation to $7.8 billion by the end of 2019. Let’s dig deep into Datadog to know its competitors.

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?