AUTOMATE Automate your data pipelines Integrate Wherobots into your data workflows for full automation and optimal performance. Try Wherobots Now Automate Spatial ETL Orchestrate Wherobots from your existing pipelines with full observability. Integrate with Apache Airflow Plug into your existing Airflow pipelines with Wherobots’ Apache Airflow Provider. Accelerate your Existing Pipelines Migrate existing Apache Spark and Sedona pipelines to improve performance and lower costs. Orchestrate with Apache Airflow Use Wherobots’ Airflow Provider to run a Wherobots job or execute Spatial SQL in new or existing Airflow DAGs. Available for Wherobots Professional and Enterprise Editions. Learn More Or integrate with the Job Runs API Wherobots’ Job Runs REST API provides full flexibility, allowing you to trigger and monitor Wherobots Jobs. Learn More Run your existing workflows more efficiently Seamlessly migrate your existing Apache Spark and Sedona workflows and tasks to Wherobots and instantly benefit from higher performance and lower costs. Learn more Observability Track performance and monitor the health of your automated data processing. Full visibility enabled with overall usage, job status, logs and metrics. Job Runs Workload Usage Logs & Metrics Learn more about monitoring job runs Learn more about monitoring your workload usage FAQ How do I use Wherobots with Apache Airflow? You can install the Wherobots Apache Airflow provider (with pip install airflow-providers-wherobots), or add it as a dependency to your Apache Airflow application. After you create a connection to Wherobots from your Airflow Server, and configure your Wherobots API key, you can use the following operators: WherobotsRunOperator: to execute Python or JAR job runs on the Wherobots Cloud. WherobotsSqlOperator: to execute Spatial SQL queries on Wherobots Cloud. Note: Available for Wherobots Professional and Enterprise Edition. What kinds of code can a Wherobots Run execute? A Wherobots Run can be configured to execute either a Python file or a JAR file stored on an accessible S3 path (via Managed Storage or Storage Integration). When creating a run, you must specify a required runtime (e.g., tiny, medium, x-large-himem). You can also specify custom dependencies to be included in the environment, such as PyPI packages or other dependency files. Note: Available for Wherobots Professional and Enterprise Editions What types of workloads can be migrated to Wherobots? Existing Apache Spark and Sedona workloads can be migrated seamlessly to Wherobots. You can leverage your existing code without changes and instantly benefit from improved performance and reduced costs. Get started Modernize your spatial data in the lakehouse today. request demo try wherobots now
