Manta vs Databricks
Side-by-side comparison of AI visibility scores, market position, and capabilities
Manta is an automated data lineage platform that traces data flows across the full technology stack, providing impact analysis and compliance documentation for enterprise data teams.
About
Manta is an automated data lineage platform that traces the complete flow of data across an enterprise's technology stack — from source databases and files through ETL tools, data warehouses, data lakes, BI platforms, and application code — by parsing the technical artifacts that define data transformations (SQL code, ETL job configurations, stored procedures, and application logic) and constructing a comprehensive lineage graph that documents every transformation step data undergoes from origin to consumption. Unlike catalog platforms that capture lineage only from query logs or metadata APIs, Manta's code-parsing approach captures lineage from the actual transformation logic even for data flows that are not logged at runtime, providing complete lineage coverage for complex enterprise environments with heterogeneous transformation tooling that mixes SQL, stored procedures, custom ETL code, and BI tool calculations.
$4.8B revenue run-rate; 55% YoY growth; $134B valuation (Series L). Mosaic AI for enterprise LLM fine-tuning and inference; Unity Catalog for data governance. DBRX open-source model; every major enterprise AI deployment runs on the lakehouse.
About
Databricks was founded in 2013 by the original creators of Apache Spark — Ali Ghodsi, Matei Zaharia, and five other UC Berkeley researchers — to unify data engineering, analytics, and machine learning on a single platform. The company commercialized the lakehouse architecture, combining the flexibility of data lakes with the reliability of data warehouses. Databricks runs on AWS, Azure, and GCP and leads the commercial distribution of the open-source Delta Lake and MLflow projects.\n\nThe platform includes the Databricks Lakehouse for unified data processing, Unity Catalog for governance and lineage tracking, and Mosaic AI for enterprise LLM fine-tuning, model serving, and generative AI application development. It supports data engineering, SQL analytics, BI, feature engineering, and model training within a single governance perimeter, serving enterprises in financial services, healthcare, manufacturing, and media.\n\nDatabricks achieved a $4.8 billion annualized revenue run-rate in early 2025 with 55% year-over-year growth and a $62 billion valuation from its Series L round — one of the most valuable private software companies globally. Its dual role as the leading commercial lakehouse vendor and steward of influential open-source projects gives it a unique ecosystem advantage as enterprises accelerate investment in AI infrastructure.
AI Visibility Head-to-Head
Key Details
Capabilities & Ecosystem
Also Compare
Track AI Visibility in Real Time
Monitor how your brand performs across ChatGPT, Gemini, Perplexity, Claude, and Grok daily.