![]() ![]() In particular, there is a big difference between storage engines that are optimized for transactional workloads and those that are optimized for analytics. While this might look like getting into a low level territory of dealing with database internals, application developers who don't work with database internals directly still need to understand the main differences between data structures used in the storage engines of different databases to be able to not just select the suitable database for their application business usecase, but also the suitable storage engine for their database. ![]() Why Should I as an Application Developer care about Storage Engines? In later articles we will discuss more topics related to storage and retrieval, mainly, transactions processing and column-oriented storage. ![]() This chapter is pretty long so we will discuss it over a series of articles, this one will discuss the data structures commonly used for storage such as hash indexes, SSTables, LSM-trees, B-trees, etc. Now we move on to chapter 3 which discusses storage and retrieval. In the previous two articles, we discussed chapter 2 of Designing Data Intensive Applications by Martin Kleppmann which discussed data models and query languages, here and here. ![]()
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