ETL Apache Impala data with Trifacta



Apache Impala is a modern, open source, distributed SQL query engine for Apache Hadoop.

ETL Apache Impala data to your data warehouse, such as Amazon Redshift, Google BigQuery, Snowflake, Databricks, etc., in seconds. With Designer Cloud's Apache Impala data connector, you can transform, automate and monitor your Apache Impala data pipeline in real-time. No code required.


Join Apache Impala data with any data source

Combine datasets from any data source with your Apache Impala data. Connect to any data - Designer Cloud's data integration workflow supports a wide variety of cloud data lakes, data warehouses, applications, open APIs, file systems, and allows for flexible execution, including SQL, dbt, Spark, and Python. Whether it's joining Apache Impala data with your Salesforce CRM data, an Excel CSV, or a JSON file, Trifacta's visual workflow lets you interactively access, preview, and standardize joined data with ease.

Apache Impala Screenshot

Apache Impala to your data warehouse in minutes

ETL your Apache Impala data to the destination of your choice.


No-code automation for your Apache Impala data pipeline

Designer Cloud empowers everyone to easily build data engineering pipelines at scale. With a few simple clicks, automate your Apache Impala data pipeline. No more tedious manual uploads, resource-intensive transformations, and waiting for scheduled tasks. Deploy and manage your self-service Apache Impala data pipeline in minutes not months.

Ensure quality data every time.

No matter how you need to enrich and transform data for Apache Impala, ensure that the end result is high-quality data, every time. Designer Cloud automatically surfaces outliers, missing data, and errors and its predictive transformation approach allows you to make the best possible transformations to your data.

Schedule, automate, repeat.

Automate your Apache Impala data pipelines with job scheduling so that the right data is in Apache Impala when you need it. When new data becomes available for Apache Impala, let your scheduled data pipelines do the work of preparing it for you—no manual intervention required.


"Designer Cloud allows us to quickly view and understand new datasets, and its flexibility supports our data transformation needs. The GUI is nicely designed, so the learning curve is minimal. Our initial data preparation work is now completed in minutes, not hours or days."


Use cases for the Apache Impala data connector

  • ETL Apache Impala data to Amazon Redshift

  • ETL Apache Impala data to Google BigQuery

  • ETL Apache Impala data to Snowflake

  • ETL Apache Impala data to Databricks

  • ETL Apache Impala data to MySQL

  • ETL Apache Impala data to Microsoft Azure

  • Join Apache Impala data with Google Sheets data

  • Prepare Apache Impala data for data visualization in Tableau

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