CSV, JSON, and Parquet
Read and write all three, with gzip, bzip2, and zstd on the way in.
Google Cloud Storage
Polytomic connects Google Cloud Storage to your data warehouse, databases, and SaaS tools for file based ETL and reverse ETL. Read CSV, JSON, and Parquet files into your data warehouse and other systems, and write query results back to your bucket on a schedule, without writing code.
Recursive path patterns
Match nested folders and capture parts of the path as real columns.
Natural data warehouse pairing
One of the most common ways teams load a Cloud Storage lake into a data warehouse.
Example workflows
Load Cloud Storage files into your data warehouse and other systems
What you can sync
Move data between Google Cloud Storage and your data warehouse, databases, and SaaS tools, reading files in and writing scheduled output back out.
From Google Cloud Storage
CSV, JSON arrays, JSON lines, and Parquet
Gzip, bzip2, and zstd compressed CSV and JSON
Recursive glob patterns with path values captured as columns
One file per table, many files as one table, or discovered tables
Headerless CSV and configurable skipped lines
To Google Cloud Storage
CSV, JSON lines, JSON documents, and Parquet output
Replicate mode replacing a single stable object
Snapshot mode writing timestamped objects
Incremental append writing changed records as new objects
Bucket prefix and configurable output subfolder
How it works
Point Polytomic at a bucket and it discovers the files there, infers schemas, and loads them into your data warehouse, databases, or SaaS tools. In the other direction it writes query results back to Cloud Storage on a schedule in whichever format the consuming system expects.
Path patterns are what make recurring drops workable. Patterns can recurse through nested folders, gather many files into one table, and capture parts of the path such as a date or a region into real columns rather than context that disappears on load.
- Connect with a service account key and select a bucket
- Read CSV, JSON, JSON lines, and Parquet, including compressed files
- Match files with recursive glob and capture patterns
- Group files as individual tables, one combined table, or discovered tables
- Write output as replicate, snapshot, or incremental append
- Monitor sync health, record volume, and failures from one interface
How to set up
Polytomic authenticates to Cloud Storage with a service account key, and derives the project and service account identity from it. Grant that service account access to the buckets you want to read or write, and scope the connection to a bucket and optional prefix.
How to get connected
- 1In Google Cloud, create a service account with access to your bucket
- 2Download the service account JSON key
- 3In Polytomic, navigate to Connections, then Add Connection, then Google Cloud Storage
- 4Paste the service account key and set the bucket and any prefix
- 5Add a glob or capture pattern if you want to match a set of files
- 6Test the connection and click Save
See the documentation for full setup details.
Frequently asked questions
Why teams choose Polytomic
No engineering required
Set up and manage syncs without writing code.
Flexible data modeling
Use SQL to define exactly what data gets synced.
Handles scale automatically
Supports large datasets with incremental syncs and bulk APIs.
Start syncing your data with Google Cloud Storage in minutes
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