In Data Engineer’s Lunch #8: SQL Databases part 2, we continued our discussion of relational concepts, popular SQL databases, and advantages and disadvantages. The live recording of the Data Engineer’s Lunch, which includes a more in-depth discussion, is also embedded below in case you were not able to attend live. If you would like to attend a Data Engineer’s Lunch live, it is hosted every Monday at noon EST. Register here now!
This week’s lunch was a continuation of last week’s talk on SQL databases. This week, we extended the topic to cover Cloud Databases and database tools compatible with SQL databases. The first part can be found here.
Our first topic this week was to extend the taxonomy of databases we built last week. Within this topic, we discussed using CSV files to store data as a type of filesystem or in-memory database. We also go over which of the file/in-memory databases users might still have reason to use today, as well as their advantages and disadvantages.
We then moved on to open source databases. DB-engines allowed us to analyze the different open source databases and get a relative ranking of relational databases and trends in database usage. We also covered tech stacks including open source databases that may have contributed to their relative popularity. We also briefly talked about the underlying storage engines for relational databases.
We then moved on to discussing could managed databases. We discussed their similarities in terms of the interface to normal relational databases as well as their advantages in terms of stability.
Finally, we discussed a couple of external tools for working with SQL databases.
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