Telmai vs Databricks
Side-by-side comparison of AI visibility scores, market position, and capabilities
Mountain View ML-powered data observability for raw data lakes monitoring 100% of records without sampling; $11.39M Glasswing/.406 Ventures-backed competing with Monte Carlo for data quality monitoring in open lakehouse architectures.
About
Telmai is a Mountain View, California-based AI data observability platform — backed by $11.39 million in total funding including a $5.5 million seed round co-led by Glasswing Ventures and .406 Ventures with Zetta Venture Partners — providing data engineers and data scientists with ML-powered real-time monitoring of data quality across data lakes and warehouses in raw format at scale without data sampling, offering record-level anomaly detection, data drift monitoring, and data quality scoring for open architecture environments (Apache Iceberg, Delta Lake, Hudi) that traditional data observability tools built for structured SQL warehouses cannot adequately monitor. Founded in 2020 and generating $2.6 million in revenue in 2024 (up from $1.5M in 2023) with a 14-person team.
$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.
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