San Francisco, [April 2, 2025] – Databricks has taken a major step toward streamlining enterprise data integration with the general availability of Lakeflow Connect, its new low-code/no-code connector system. The initial release features preconfigured integrations with Salesforce and Workday, with plans to expand support to additional SaaS platforms, databases, and file sources in the coming months.
Simplifying the Data Ingestion Challenge
Data ingestion—the process of moving data from source systems into analytics environments—has long been a complex, resource-intensive task for enterprises. Traditional approaches require stitching together multiple tools (such as Apache Kafka or CDC solutions) and maintaining custom pipelines, often leading to scalability issues and high operational overhead.
Lakeflow Connect aims to eliminate these pain points by providing:
- Prebuilt, low-code connectors for seamless integration with SaaS applications
- Serverless compute for automatic scaling without cluster management
- Native governance via Unity Catalog, applying security and compliance policies during ingestion
- End-to-end data engineering when combined with Delta Live Tables (DLT) and Databricks Workflows
“Customers need this data, but before Lakeflow Connect, they were forced to rely on third-party tools that often failed at scale—or build custom solutions,” said Michael Armbrust, Distinguished Software Engineer at Databricks. “Now, ingestion is point-and-click within Databricks.”
Why Salesforce and Workday First?
The choice of initial connectors reflects the growing demand for real-time, structured data to power AI and generative AI applications. According to Kevin Petrie, Analyst at BARC U.S., more than 90% of AI leaders are experimenting with structured data, and nearly two-thirds use real-time feeds for model training.
“Salesforce and Workday provide exactly the type of data needed for real-time ML and GenAI,” Petrie noted. “Databricks is smart to simplify access in this way.”
Competitive Differentiation
While other vendors offer connector solutions (e.g., Qlik’s Connector Factory), Lakeflow Connect stands out through:
- Deep Unity Catalog integration – Automatically applies governance policies to ingested data.
- Change Data Capture (CDC) capabilities – Inherited from Databricks’ 2023 acquisition of Arcion.
- Serverless performance – Reduces latency and scales dynamically for complex pipelines.
“Serverless compute is quietly important,” said Donald Farmer, Principal at TreeHive Strategy. “It’s not just about scalability—rapid startup times are critical for reducing pipeline latency.”
The Road Ahead
Databricks has already outlined plans to expand Lakeflow Connect with connectors for:
- Google Analytics
- Microsoft SQL Server
- Oracle NetSuite
- PostgreSQL
- ServiceNow
- SharePoint
Though the company hasn’t committed to a timeline, Armbrust hinted at upcoming announcements at the Data + AI Summit in June.
Broader Vision: Democratizing Data Engineering
Beyond ingestion, Databricks is focused on unifying the data engineering lifecycle. “Historically, you needed deep Spark or Scala expertise to build production-grade pipelines,” Armbrust said. “Now, we’re enabling SQL users—or even UI-only users—to achieve the same results.”
Looking further ahead, Petrie suggested Databricks could enhance cross-team collaboration for agentic AI development, integrating Lakeflow with Mosaic AI and MLflow to bridge data, model, and application lifecycles.
The Bottom Line
Lakeflow Connect marks a strategic move by Databricks to reduce friction in data pipelines—addressing a key bottleneck for enterprises scaling AI initiatives. As the connector ecosystem grows, it could further solidify Databricks’ position as an end-to-end platform for data and AI.
For more details, visit Databricks.com.
Key Takeaways:
✅ Now Available: Salesforce & Workday connectors
✅ Serverless, governed, and scalable ingestion
✅ Future integrations with Google Analytics, ServiceNow, and more
✅ June previews expected at Data + AI Summit
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