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The Delta Lake connector allows ingestion from a Delta Lake data platform hosted in S3 and GCS into Pinot. The ingestion is done as a periodic pull based system that is executed by the Pinot Minion framework. You specify the period that you want the ingestion task to follow and on each trigger Minion will check if there has been a change to the Delta Lake since the last execution and, if there has, it will ingest the new data. StarTree’s Delta Lake connector supports both the older Standalone Delta Lake API(v3.3.2) and the new Delta Kernel API(v4.0.0). With the Delta Kernel API, the StarTree Delta Lake connector also supports the use of Deletion Vectors.

Prerequisites

  • Delta Lake ingestion can only be enabled for offline Pinot tables
  • This connector supports Delta tables hosted on Amazon S3 and Google Cloud Storage(GCS).
  • This connector supports only sync mode, meaning each file in Delta Lake maps to a single segment in Pinot. Therefore, it is recommended to size the files appropriately to avoid creating an excessive number of segments. Find the official documentation on how to tune the size of files in your Delta table.

Limitations

  • Support for ADLS is not yet available.
  • Delta tasks do not utilize checkpoints. Consequently, no table entry is created at the ZK path PROPERTYSTORE→MINION_TASK_METADATA. This limitation applies to both Delta Standalone mode and Delta Kernel mode. Tasks will fail if not completed within one day, as Delta does not track progress. Subsequent triggers will generate new tasks to resume processing.

Pinot Table Configuration

The offline table task configs can be manually set with the following connection and ingestion parameters.

Connection Parameters

All the following properties are required to establish connection with Delta Tables.

Authentication Parameters

Delta Tables hosted on S3 via Basic Authentication

Use the following JSON configuration when Delta is set up on S3 with Basic Authentication

Property Descriptions

Delta Tables hosted on S3 via IAM based Authentication

Property Descriptions

If you are using IAM to managed access to your S3 bucket then, use the following parameters:

Delta Tables hosted on GCS

Use the following JSON configuration when Delta is set up on GCS

Property Descriptions

Frequently Asked Questions

StarTree uses Delta Kernel Library to get the updated list of files and uses the Minion framework to manage data segments. Every time a row is added, updated, or deleted in Delta, the underlying files change, which updates the table version. Pinot detects these changes and updates its corresponding table segments accordingly — ensuring the latest state is always reflected.If there are 1M rows in a table and only one row is updated. This will result into update in one segment only since file and segment has 1:1 mapping. In other words,
  • If all 1M rows are stored in a single file and hence one single segment, the entire segment will be replaced even if just one row changes.
  • If the 1M rows are split across 10 files, only the relevant segment (1 out of 10) mapped to the particular file containing the updated row will be replaced.
This ensures Pinot always reflects the latest state while maintaining efficient resource usage, depending on how the segments are structured.
Yes, you can. Pinot supports high-frequency scheduling, including a 1-minute refresh. This will create one ingestion task per minute. However, if you’re targeting sub-minute or near real-time updates, a streaming ingestion approach may be more efficient.
Not at the moment. Unity Catalog support is currently not available in the Delta Kernel libraries, so Pinot doesn’t support it either. As a workaround, you can filter out restricted columns while creating the Pinot table.
No. Pinot uses an internal watermark system via Zookeeper to avoid scanning all files every time. It only checks for new files added after the watermark. DeltaIngestionTask (Delta ingestion) relies on Delta’s transaction logs. Starting from version 1.3.0, it no longer uses a watermark — it simply applies the differences between versions.
Yes, We now support column mapping with both NAME and ID mode.