Frankly speaking ...

Ever wonder what's really happening behind the scenes of your favorite apps, streaming services, or even your smart fridge? It's all about data, and the databases that manage it. We swim in an ocean of it, a veritable deluge that is only getting deeper. Consider that in 2023 alone, the amount of data created, captured, copied, and consumed globally reached 120 zettabytes. Databases are the unsung heroes, the silent MVPs making sense of this chaos. But the era of the "digital filing cabinet" is over. Databases are undergoing a massive transformation, moving from rigid, monolithic systems to incredibly flexible, intelligent, and specialized powerhouses. In this post, I explore some of the most surprising developments in this landscape—from the resurgence of SQL and the rise of "embedded" engines that live inside your apps, to the fusion of databases with AI and the Git-like ability to "branch" your data. Read on to discover why the future of database...

During a recent conversation I started to think about the various types of databases now available. What types are there? What are they used for? In a later article I will explore developments in databases. Relational Database Management Systems (RDBMS) Relational databases model data using rows and columns organised into a series of tables. This architecture became dominant in the 1980s. The design involves splitting data into a set of normalised tables, or relations , which aims to ensure that each elementary "fact" is stored only once, thereby simplifying update operations and helping to maintain consistency. The vast majority of these databases use Structured Query Language (SQL) for querying and writing data. Compared to non-relational databases, RDBMSs typically provide strong consistency (also known as immediate consistency). Examples of Use: Relational systems dominate large-scale data processing applications. Specific implementations like PostgreSQL are often ut...