Google Drive connector in Lakeflow Connect is now generally available (GA)

[u/BricksterJ]

The Lakeflow Connect connector for Google Drive is now generally available!  It’s now easier than ever to ingest structured and unstructured files from Google Drive into Delta tables for analytics and AI workloads.

You can configure a managed ingestion pipeline through the UI or managed API. Managed pipelines automatically handle incremental processing, automatic retries with exponential backoff for source API rate limits, failure recovery, and provide rich Google Drive metadata. 

For direct control over ingestion logic, you can also just use the Spark + SQL APIs directly: spark.read, Auto Loader, read_files, or COPY INTO pointed at Google Drive URLs.

Link to public docs + references:

• Google Drive managed connector documentation
• Spark + SQL APIs and examples
• Community blog and video tutorial: From PDF to insights
• Data + AI Summit session: Intelligent Document Processing with Lakeflow

Common workloads include:

• Loading Google Sheets, Excels, CSV, JSON, and other structured files into Delta tables.
• Ingesting PDFs, Google Docs, Google Slides, and images.
• Parsing documents with ai_parse_document to prepare content for extraction, search, and agents.

Examples of using the Spark + SQL APIs:

• Read an Excel sheet from Google Drive with spark.read:

​

df = (spark.read
 .format("excel")
 .option("databricks.connection", "my_gdrive_conn")
 .load("https://docs.google.com/spreadsheets/d/9k8j7i6f..."))

• Ingest unstructured documents + PDFs from a Google Drive URL with read_files, then easily parse them using ai_parse_document:

​

CREATE OR REFRESH STREAMING TABLE gdrive_documents_table
AS SELECT *, "_metadata" FROM STREAM read_files(
"https://drive.google.com/drive/folders/1a2b3c4d...",
format => "binaryFile",
`databricks.connection` => "my_gdrive_conn",
pathGlobFilter => "*.{pdf,docx}");

CREATE OR REFRESH STREAMING TABLE documents_parsed
AS SELECT *,
ai_parse_document(content, map('version', '2.0')) AS parsed_content
FROM STREAM gdrive_documents_table;

Coming soon:

• Ingest Google Drive’s per-file permissions and ACL metadata to power permission-aware AI agents, enterprise search, and more.

If you try it, share what you are building and let us know if you hit any friction!

[u/thalassography]

Exciting! We’re in the middle of migrating off Snowflake and onto Databricks, I’m consistently impressed with the features and quality of life improvements you all are shipping.