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Delta Lake: Cloud Service for Fast Big Data Analytics

Data lakes help companies consolidate data sources that require processing. Often, the data stored in the data lakes is unreliable, and the data lakes themselves are disorganized. Therefore, Databricks decided to release its open-source Delta Lake solution.

Delta Lake is the most popular format for lake houses worldwide, and its popularity among data engineers is growing.

What is Delta Lake Format?

Delta Lake is an open-source storage layer that guarantees data consistency, isolation, and durability in the lake. It is a cloud ready project used by many large companies around the world. Databricks has opened Delta Lake's platform code to help businesses structure different sources of information into lakes with reliable and manageable data.

What are the Main Benefits of Delta Lake implementation?

Companies require high-quality transactional support to ensure their data reliability. The lack of it prevents businesses from getting the most out of their data lakes.

With Delta Lake, users can access earlier versions of their data for reconciliation. They can roll back transactions or reproduce Machine Learning experiments.

What does Delta Lake offer, and is the solution a new data standard, a tool, or both?

  • Delta Lake provides ACID (Atomicity, Consistency, Isolation, Endurance) transaction support through optimistic concurrency control.

  • Delta Lake isolates snapshots to hide junk data during recording.

  • Delta Lake provides support for Data versioning.

  • Delta Lake makes data rollback.

  • Delta Lake applies schemes to better handle data types.

Delta Lake platform is a fully open solution and does not require integration with other Databricks solutions. It aims to standardize big data formats stored locally and in the cloud. This is necessary to prepare data lakes for analytics and machine learning, so Databricks chose an open storage format and transaction protocol for Delta Lake. They are designed to manage transactions, including streaming and batch read and write jobs to move data to and from Delta Lake. These capabilities help to improve the reliability of these lakes.

Why do you need Delta Lake?

Data lakes have many advantages, but some challenges arise with increasing amounts of data stored in a single data lake:

ACID transactions. If the pipeline fails when writing data to the lake, it leads to partial recording or data corruption. Delta Lake is ACID compatible. The write operation will complete or will not complete at all, thus avoiding recording corrupted data.

Unified batch, stream sources and sinks. Developers write business logic separately for the streaming and batch pipelines using different technologies. In addition, they cannot have simultaneous read and write jobs for the same data.

With Delta Lake, the same features can be applied to batch and streaming data. Any change in business logic ensures consistency between the two sinks. This service also allows users to read consistent data, while new data is downloaded using structured streaming.

Schema application and evolution. Incoming data schema can change over time. In a data lake, this can lead to data type incompatibility or corrupted data. Delta Lake helps users avoid getting into the table of another pipeline of incoming data and damaging it. This service also allows users to revert to an older version of the data to correct wrong updates, deletions, and other transformations that resulted in incorrect data.

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