Databricks to acquire Tabular for one billion dollar

Databricks is a data and an AI company founded in 2013 by the creators of Apache Spark. Every company now deals with tons of structured and unstructured data. These companies need a way to store and retrieve useful information from their data. Databricks has multiple products to address the need for the customers.

Tabular is a small startup which helps to store data in optimized way using Apache Iceberg. Tabular is founded in 2021 by the Apache Iceberg creators Ryan Blue and Dan Weeks. Apache Iceberg is a high-performance open source format for analytic tables. Ryan Blue and Dan Weeks created Apache Iceberg while working at Netflix to solve the problems related to data lake, its performance and correctness in data engineering. It was later donated to Apache Foundation. 

Databricks is to acquire Tabular for around one billion dollar. As the company started in 2021 and within short duration, Tabular made it big, their adoption rate is high among the companies. This is really great and it is a Win-Win situation for both Databricks and Tabular. Tabular team contributes to open source Apache Iceberg community and they will continue to do so.

Apache Iceberg is basically a data storage platform where it helps to store and retrieve information from large data set. It supports SQL query to retrieve required information from the data set. Most of the big companies need data lakes to store data and Apache Iceberg handles it better. To solve data lake storage issue, Databricks built an open source project Delta Lake around similar time frame when Ryan Blue and Dan Weeks started working on Iceberg. Both Delta Lake and Iceberg are built on top of Apache Parquet format and their design goals are similar. Now Databricks has two similar products but they are not compatible to each other as it has been built by independent teams.

Data is new oil, Companies with huge amount of data are striving hard to manage their data lake. Databricks has diverse products and solutions to cater the needs of data engineering.