Connecting Your Databricks & Impala Data
Whether you’re integrating Databricks with Impala or moving data from one of these solutions to the other, getting your information where it needs to be is crucial. Use StarfishETL’s robust iPaaS to connect your data with speed and flexibility.
Secure Connections Between Databricks to Impala
The iPaaS powering your Databricks and Impala connection not only provides unrivaled scalability, but also offers strict security protocols to keep data safe as it moves across applications. StarfishETL applies two-fold data security between Amazon Web and our internal servers to maintain the highest levels of protected infrastructure. Strict data encryption practices and progressive security principles keep sensitive information secure at all times as it passes between Databricks and Impala.

Databricks and Impala Integration
Integrate Databricks and Impala to boost your analytical power, align your teams, and create more omnichannel experiences across your business. StarfishETL makes the process seamless with a library of pre-configured maps at your fingertips and easy ways to customize your project. Check out the visual below to learn how a typical integration flows. Then, contact our team to request a quote on your Databricks and Impala project.

Set up access to each system

Define processes & stages

Modify integration & add custom fields

Test integration

Run initial data migration load

Ensure keys are matching between systems

Start integration
Ready to Connect?
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About These Solutions
Databricks is a big data processing platform that was founded by the creators of Apache Spark. Meant to accelerate development and innovation, Databricks provides an incredibly fast, just-in-time, cloud-based platform for big data processing. The solution is primarily used for data science projects involving AI and Machine Learning in the enterprise.
Apache Impala is a modern, open-source, Massive Parallel Processing (MPP) SQL query engine used for analyzing and processing data stored in the Hadoop cluster. Impala is designed for speed and can process data stored in FDFS lightning-fast. Its interactive queries can read nearly all file formats such as Parquet, Avro, and RCFfile used by Hadoop.
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