What issues Delta lake solve

A Data lake is a centralized repository for all your data, regardless of its format or source. It is a way to store large amounts of data in its raw format, without having to first clean or transform it. This can be useful for storing data from a variety of sources, such as sensors, social media, and transactional systems.

Delta Lake is an open-source storage layer that builds on top of a data lake. It adds a transaction log, which allows data lake users to have access to features that are common in databases, such as ACID transactions, schema evolution, and time travel.

Delta Lake came into existence because of the limitations of traditional data lakes. Traditional data lakes are not ACID compliant, which means that data can be inconsistent if multiple users are accessing it at the same time. They also do not support schema evolution, which means that you cannot change the schema of your tables without losing data. Additionally, traditional data lakes do not provide time travel capabilities, which means that you cannot view and restore earlier versions of your data.

Delta Lake addresses these limitations by providing ACID transactions, schema evolution, and time travel capabilities. This makes it a more reliable and scalable way to store data in a data lake.

Here is a table of the key features of data lakes and Delta Lake:

As you can see, Delta Lake provides a number of features that are not available in traditional data lakes, such as ACID transactions, schema evolution, and time travel. These features make Delta Lake a more reliable and scalable way to store data in a data lake.