You wouldn’t think there’d be so much fanfare – and such colossal budgets – around data storage. And yet there are 6 public companies in the U.S. that have built billion+ dollar database businesses, from $ORCL to $ESTC to $SNOW. Not to mention the public clouds that sell database products ($AMZN, $GOOG, $DOCN, etc.), plus supporting tooling for infrastructure ($DDOG, $NEWR, etc.).
How should you understand the differences between all of these seemingly similar databases? What do developers actually use databases for anyway? And why would one be better than another?
This post will run through everything that an investor needs to know to effectively understand the difference between different databases and how they’re positioned in the market. So far in this category, we’ve covered Elastic, MongoDB, Snowflake, and Confluent, plus AWS.
If you’re still getting up to speed on what databases are, you’ll want to read Technically’s beginner's guide to databases. We also have more in depth posts on a few of the categories listed there, like production databases,relational databases, NoSQL databases, and more.
You can also refer back to the database database if you like having a cheat sheet.