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Persistent storage & databases

Persistent storage is any method of storing data that remains intact and accessible even after a system is powered off, restarted, or experiences a crash.

The recommended approach is to use data tables to store relational data, and ducklakes to store massive datasets, with external databases available as resources.

Built-in relational database functionality requiring minimal setup for storing structured data directly within Orvanta.

A data lakehouse solution enabling massive amounts of data stored in parquet files on S3 while querying it with natural SQL syntax.

Connect existing databases through integrations or create custom resource types if your provider isn’t pre-integrated.

Large unstructured data: S3, Cloudflare R2, MinIO, Azure Blob Storage, and Google Cloud Storage are highly scalable and durable object storage services with native Orvanta integration.

Structured SQL data: Postgres-based solutions like Supabase and Neon.tech are recommended for schema-based storage with defined entity relationships.

File persistence: Volumes provide persistent file storage that can be attached to scripts, with automatic syncing to object storage between runs.

NoSQL solutions: MongoDB Atlas, Redis, and Upstash support flexible, non-structured data management.

Orvanta offers internal persistence between job executions, but this approach is explicitly marked as not recommended.