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A unified analytics platform, powered by Apache Spark
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What is Databricks?

Databricks Unified Analytics Platform, from the original creators of Apache Spark™, unifies data science and engineering across the Machine Learning lifecycle from data preparation to experimentation and deployment of ML applications.
Databricks is a tool in the General Analytics category of a tech stack.

Who uses Databricks?

12 companies reportedly use Databricks in their tech stacks, including, QuintoAndar, and TruSTAR Technology.

28 developers on StackShare have stated that they use Databricks.

Databricks Integrations

Kafka, TensorFlow, Hadoop, Apache Spark, and Keras are some of the popular tools that integrate with Databricks. Here's a list of all 12 tools that integrate with Databricks.

Why developers like Databricks?

Here’s a list of reasons why companies and developers use Databricks
Top Reasons
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Databricks's Features

  • Built on Apache Spark and optimized for performance
  • Reliable and Performant Data Lakes
  • Interactive Data Science and Collaboration
  • Data Pipelines and Workflow Automation
  • End-to-End Data Security and Compliance
  • Compatible with Common Tools in the Ecosystem
  • Unparalled Support by the Leading Committers of Apache Spark

Databricks Alternatives & Comparisons

What are some alternatives to Databricks?
Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.
Azure Databricks
Accelerate big data analytics and artificial intelligence (AI) solutions with Azure Databricks, a fast, easy and collaborative Apache Spark–based analytics service.
Use our cloud-hosted infrastructure to securely run your code on powerful hardware with a single command — without any changes to your code. If you have your own infrastructure, our Enterprise offering provides powerful, easy-to-use cluster management functionality behind your firewall.
It is a data streaming platform based on Apache Kafka: a full-scale streaming platform, capable of not only publish-and-subscribe, but also the storage and processing of data within the stream
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
See all alternatives

Databricks's Followers
36 developers follow Databricks to keep up with related blogs and decisions.
Anand Chockalingam
Allison Howells
Pasi Koski
Doug Bunting
Partha Roy
Ajay Ramkrishnan
Abir Sarkar
Amitabh Tewari
Timothé DELION