Databricks Lakewatch vs Scanner: Side-by-Side Comparison (2026)

Databricks Lakewatch: Open agentic SIEM on Databricks lakehouse for petabyte-scale SOC ops. built by Databricks. Core capabilities include Agentic AI-driven threat detection and response, Petabyte-scale security data ingestion and storage, Unified security data lakehouse architecture..

Scanner: Security data lake platform for threat detection via S3-native log indexing. built by Scanner. Core capabilities include S3-native log indexing with no data movement required, Continuous real-time threat detection on full data stream, Historical log search across years of data in seconds..

Both serve the Security Information and Event Management market but differ in approach, feature depth, and target audience.

Databricks Lakewatch differentiates with Agentic AI-driven threat detection and response, Petabyte-scale security data ingestion and storage, Unified security data lakehouse architecture. Scanner differentiates with S3-native log indexing with no data movement required, Continuous real-time threat detection on full data stream, Historical log search across years of data in seconds.

Databricks Lakewatch is developed by Databricks. Scanner is developed by Scanner. Vendor maturity, funding stage, and team size can be important factors when evaluating long-term viability and support quality.

Databricks Lakewatch integrates with Databricks Unity Catalog, Databricks Delta Lake, Databricks Delta Sharing, AWS, Azure and 1 more. Scanner integrates with AWS CloudTrail, Azure, Google Cloud, Okta, GitHub and 2 more. Check integration compatibility with your existing security stack before deciding.

Databricks Lakewatch and Scanner serve similar Security Information and Event Management use cases: both are Security Information and Event Management tools, both cover Log Management, Detection Rules, AI SOC. Review the feature comparison above to determine which fits your requirements.