DATABRICKS vs SPARK

Comparison between two different big data tools used for solving complex big data problems.

SPARK

1. Open source framework for data analysis and data processing.
2. Spark has replaced MapReduce by providing advantages in terms of memory and fast processing of data.
3. Spark code can be written in Java, Python, R, and Scala.
4. Older versions of spark work with RDD(basic and smallest unit for dataset) which is replaced by data frames in the latest versions.
5. Need installation and setup to work with Spark.

DATABRICKS

1. Databricks is a company founded by Apache Spark Authors.
2. It is a cloud platform that provides analytical services. Build on top of apache spark with lots of advantages of the web interface, Notebook, Rest API, cluster management, cluster scaling, etc...It allows users to develop, run and share Spark-based applications.
3. Databricks company claims to optimize spark by itself which can be used to get things done quickly and efficiently.
4. No need to install the spark cluster is provided by data bricks.

Note: Databricks community free edition is available for 1 year.