Azure Blob Storage pipelines,
described in plain English.
Land PostgreSQL, MySQL, and SaaS data in Azure Blob as Parquet, JSON, or CSV — CDC streaming or scheduled snapshots — and move raw files byte-for-byte between Azure, S3, and GCS. Live on rsync.ai Cloud, no per-row fees.
rsync.ai writes to Azure Blob Storage two ways: structured output (Parquet, JSON, or CSV with a schema manifest, from Postgres/MySQL CDC or snapshots, ADLS Gen2 partitioned for Synapse and Fabric) and byte-identical blob passthrough (copy any object between Azure, S3, and GCS). Authenticate with an access key, SAS token, or managed identity; PII columns are masked before the write.
- Parquet, JSON, or CSV — ADLS Gen2 & Hive partitioning
- CDC streaming or scheduled snapshots — or both
- SAS token or managed-identity auth
- Blob passthrough between Azure Blob, S3, and GCS
Move data into Azure Blob
Start from a database, or describe any other source in plain English.
What the Azure Blob connector does
Structured exports for analytics, and raw blob passthrough for everything else.
Structured exports
Postgres & MySQL tables to Parquet, JSON, or CSV with a schema manifest.
Blob passthrough
Copy any object byte-for-byte between Azure, S3, and GCS — SHA-256 verified.
PII-safe
Mask or hash sensitive columns before a single byte lands in your container.
rsync.ai vs. Fivetran, Airbyte, custom scripts for Azure Blob
What you give up — and gain — choosing rsync.ai for pipelines into Azure Blob Storage.