Destinations

Destinations for any API, plus a wide variety of data repositories: warehouses, databases, lakes and queues.

Analytical vs. transactional

There is no one-size-fits-all solution when it comes to databases, data lakes and data warehouses. Each has different benefits and drawbacks.

Analytical data stores (OLAP) include the data warehouse vendors such as Snowflake, Redshift and BigQuery. They are normally columnar databases optimized for storing vast amounts of data at a decent price while letting you issue complex queries to understand your business data. Using one of these for operational workloads with lots of updates would be costly and inefficient.

Transactional data stores are used for operational workloads such as managing all the data from a web application. Examples are MongoDB, PostgreSQL and MySQL. These databases can handle a huge volume of updates as users interact with the product.