What is Delta Lake?

Delta Lake is an open-source storage layer that delivers reliability to data lakes. Delta Lake implements ACID transactions, scalable metadata handling, and unifies the streaming and batch data processing. Delta Lake architecture runs on top of your current data lake and is fully cooperative with Apache Spark APIs.

Why Delta Lake?

Are we making progress? Well, let’s see what are the main benefits of implementing a Delta Lake in your company.

The Predicament with current Data Architectures

Current big data architectures are challenging to develop, manage, and maintain. Most contemporary data architectures use a mix of at least three varying types of systems: streaming systems, data lakes, and data warehouses. Business data comes through streaming networks such as Amazon Kinesis or Apache Kafka, which mainly focus on accelerated delivery. Then, data is collected in data lakes, such as Apache Hadoop or Amazon S3, which are optimized for large-scale, ultra-low-cost storage. Lamentably, data lakes individually do not have the performance and quality required to support high-end business applications: thus, the most critical data is uploaded to data warehouses, which are optimized for significant performance, concurrency, and security at a much higher storage cost than data lakes.

Delta Lake architecture, Lambda Architecture

Lambda architecture is a traditional technique where a batch system and streaming system prepare records in correspondence. The results are then merged during query time to provide an entire answer. Strict latency requirements to process old and newly formed events made this architecture famous. The key downside to this architecture is the development and operational overhead of maintaining two different systems. There have been efforts to ally batch and streaming into a single system in history. Companies have not been that victorious though in those attempts. With the arrival of Delta Lake, we are seeing a lot of our clients adopting a simple constant data flow model to process data as it comes. We call this architecture, The Delta Lake architecture. We cover the essential bottlenecks for using a continuous data flow model and how the Delta architecture resolves those difficulties.

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