Apache Pinot Destination

Apache Pinot is a column-oriented, open-source, distributed data store written in Java. Pinot is designed to execute OLAP queries with low latency. It is suited in contexts where fast analytics, such as aggregations, are needed on immutable data, possibly, with real-time data ingestion. The name Pinot comes from the Pinot grape vines that are pressed into liquid that is used to produce a variety of different wines. The founders of the database chose the name as a metaphor for analyzing vast quantities of data from a variety of different file formats or streaming data sources.

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The different types of destinations

There is no one size fits all solution when it comes to databases, datalakes and data warehouses. Each one had different benefits and drawbacks which you can read more about here

Analytical vs Transactional

Analytical Data Stores (OLAPs)

The analytical data stores include normally all of the data warehouse vendors such as Snowflake, Redshift, Bigquery and many others. Analytical data stores are normally columnar data bases which are optimized for storing vast amounts of data at a decent price while at the same time allowing you to issue complex queries to understand your business data.
Using one of this solutions for operational queries where a lot of updating happens would be costly and inefficient.

Transactional Data Stores

Transactional Data Stores are more commonly used for operational workloads such as managing all the data from a web application. Common web solutions such as Wordpress rely on these type of data stores. Some examples are MongoDB, Postgresql, MySQL and many others.
These type of data bases can handle a huge volume of updates as users interact with the product.