Delta Lake

What it is

Delta Lake is a storage layer that brings scalable, ACID transactions to Apache Spark and other engines. It ensures data reliability and consistency in big data environments.

Delta Lake stands out by providing robust transactional support and data versioning capabilities specifically tailored for Apache Spark, making it a reliable choice for big data environments.

When it fits — and when it doesn’t

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

1. 01

   Steep learning curve for non-Scala developers

   Delta Lake's primary language is Scala, which can be challenging for developers primarily working with other languages like Python or Java.

2. 02

   Limited native support for languages other than Scala and Python

   While Delta Lake supports Scala and Python natively, support for other languages is limited and often relies on community-maintained libraries which may not be as robust or up-to-date.

3. 03

   Performance overhead due to ACID transactions

   Enabling ACID transactions can introduce performance overhead, especially in large-scale environments where every transaction needs to be validated and committed atomically.

4. 04

   Complex setup and configuration requirements

   Setting up Delta Lake requires configuring Spark clusters, managing storage layers, and ensuring compatibility with other big data tools, which can be complex and time-consuming.

What it does well

• ACID transactions for big data

• Data versioning and time travel queries

• Supports structured streaming

• Optimized for performance with Spark

Pricing

Free tier

YesOpen source — free to use

Paid from

$0

Model

Flat rate

Enterprise plan

No

Pricing not independently confirmed — check the vendor’s page.