Need advice about which tool to choose?Ask the StackShare community!
CDAP vs Google Cloud Data Fusion: What are the differences?
CDAP: Open source virtualization platform for Hadoop data and apps. Cask Data Application Platform (CDAP) is an open source application development platform for the Hadoop ecosystem that provides developers with data and application virtualization to accelerate application development, address a broader range of real-time and batch use cases, and deploy applications into production while satisfying enterprise requirements; Google Cloud Data Fusion: Fully managed, code-free data integration at any scale. A fully managed, cloud-native data integration service that helps users efficiently build and manage ETL/ELT data pipelines. With a graphical interface and a broad open-source library of preconfigured connectors and transformations, and more.
CDAP and Google Cloud Data Fusion can be primarily classified as "Big Data" tools.
Some of the features offered by CDAP are:
- Streams for data ingestion
- Reusable libraries for common Big Data access patterns
- Data available to multiple applications and different paradigms
On the other hand, Google Cloud Data Fusion provides the following key features:
- Code-free self-service
- Collaborative data engineering
CDAP is an open source tool with 346 GitHub stars and 178 GitHub forks. Here's a link to CDAP's open source repository on GitHub.
Pros of CDAP
Pros of Google Cloud Data Fusion
- Lower total cost of pipeline ownership1