As data has been growing in size and demand for analyses has been increasing, the software engineering world had to focus on implementing well performing solutions that could serve the demand. This has lead to many different tools, unable to offer interoperability (or offering interoperability at a major performance cost) and effectively locking developers and companies into specific vendors. As the data engineering world has matured, proper solutions emerged that were focused on interoperability, breaking vendor barriers and empowering people with ownership and control of their data and their tools. We will see now the modern data engineering tools shifted from monolithic approaches to composable systems where developers are free to store, analyse and exchange data combining the tools that are best suited for each context, need and purpose and evolving their stack as their needs evolve.