A real estate investment company with properties all over the United States and some abroad was looking to mine massive amounts of data to leverage near real-time vacation rental information. Prices and fees can change daily so keeping up with a country-sized dataset would require a quarter of a billion requests every day. In fact, several agencies said “it can’t be done.”

Data warehouses, data lakes, and data marts are all types of data storage solutions that are designed to help organizations store and manage large volumes of data. While these solutions share some similarities and often overlap in features, there are some fundamental differences that organizations should be aware of when deciding which type of solution is best suited for their needs, or how to implement the variations.

The term ‘serverless’ can sound somewhat contradictory since serverless resources are, in fact, using servers. But the concept derives its meaning from the perspective of the business that deploys it rather than the host cloud provider managing the resources.