Databricks-Native Data Ingestion Utility
The LakeSync Accelerator provides a simple, Databricks-native way to ingest files from ADLS Gen2 directly into Delta Lake tables governed by Unity Catalog with minimal configuration and no custom engineering.
Seamlessly Sync Data from Azure Data Lake into Databricks
Getting data into Databricks shouldn't be complicated. Yet many organizations struggle with inconsistent ingestion patterns, manual scripts, and brittle pipelines just to move files from Azure Data Lake Storage (ADLS) Gen2 into Delta Lake.
LakeSync is designed specifically for Databricks environments. It operates entirely within the lakehouse, eliminating the need for external tooling, complex orchestration, or bespoke ingestion code.
If your data already lives in Azure Data Lake and your analytics run on Databricks, LakeSync provides a clean, supported path to rapidly bring that data into Delta Lake.
LakeSync simplifies and standardizes file ingestion by:
- Reading files directly from ADLS Gen2
- Supporting common file formats such as CSV, JSON, Parquet, Avro and IoT Data Stream rules
- Automatically generating appropriate metadata table schemas
- Writing data directly into Unity Catalog-managed tables
Designed for Reliable Lakehouse Ingestion
Simple configuration
Get started quickly with minimal setup by defining the parameters of your source data files.
Broad file format support
Ingest unstructured data records including CSV, JSON, Parquet and Avro.
Optimized for Delta Lake
Automatically convert ingested files into Delta Lake tables enabling performance optimizations and ACID guarantees.
Unity Catalog ready
Write directly into governed tables, expanding secure and auditable access to your data across the enterprise.
Databricks-native
Runs entirely within Databricks—no external clusters, no third-party vendor tools to manage.
Available on the Databricks Marketplace
LakeSync is a valid, certified solution directly available from the Databricks Marketplace, making it easy to deploy, evaluate, and integrate into your existing Databricks workspace.
