Use Aqueduct's API to deploy workflows onto your Apache Airflow cluster but with deeper visibility.
Conda gives you strong Python environment isolation, so you can use your favorite libraries.
Launch Aqueduct workflows on top of the Databricks' Jobs API for on-demand Spark clusters.
Launch Aqueduct operators as Kubernetes pods with full control over what resources you use.
Use Lambda's serverless functions to run your Aqueduct workflows with no configuration.
Run Aqueduct workflows on your existing Spark clusters to scale your machine learning.
Use Ray to distribute your Python execution from your Aqueduct workflows.
Google Cloud's serverless functions allow you to run code with no configuration.
AWS Athena allows you to run scalable SQL queries over data stored in your S3 buckets.
BigQuery is Google Cloud's scalable cloud data warehouse.
Use Google Cloud Storage for object storage within the GCP ecosystem.
MariaDB is an open-source fork of MySQL with a fully-compatible MySQL API.
MongoDB gives you scalable, flexible document storage in the cloud.
MySQL is one of the world's most popular relational databases.
Postgres is the world's most popular open-source RDBMS.
AWS Redshift is a highly-scalable data warehouse.
AWS S3 is a highly-scalable, extremely flexible object storage system.
Snowflake is a highly-scalable cloud data warehouse that runs across clouds.
SQLite is a powerful, in-process relational database.
AWS DynamoDB is a low-latency key-value and document database.
Redis is an open-source in-memory database and caching layer.
The first storage framework that enables you to architect a Lakehouse.
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