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Stemma was acquired by Teradata.
Brief
Stemma

Stemma

Stemma provided automated data discovery and cataloging that helped data teams quickly understand their data landscape, improve data trust, and accelerate analytics workflows through intelligent metadata management.

stemma.aiSan Francisco, California, United StatesFounded 2020

Last updated May 11, 2026 by ATDb automated enrichment

Industry
Data Infrastructure/Management
Business Model
SaaS
Target Market
Mid-Market, Enterprise
Employee Count
11-50
Funding
$4.8M
Parent Company
Teradata
API Available
Yes
Customer Data PlatformData Management Platform
Market Position

Emerging player in data catalog and discovery space before acquisition by Teradata

Overview

Stemma was a data discovery and catalog platform founded to help data teams understand, trust, and collaborate around their data assets. The company provided automated metadata management, data lineage tracking, and collaborative features that enabled organizations to build a comprehensive understanding of their data landscape. Stemma's platform integrated with modern data stacks including warehouses like Snowflake and BigQuery, as well as BI tools and orchestration platforms. In August 2022, Stemma was acquired by Teradata, a leading enterprise analytics company. The acquisition was part of Teradata's strategy to enhance its data platform capabilities and expand its presence in the modern data stack ecosystem. Following the acquisition, Stemma's technology and team were integrated into Teradata's broader product portfolio, with the distinct Stemma brand and standalone product ceasing to operate independently. Prior to its acquisition, Stemma had positioned itself as a modern alternative to traditional data catalog solutions, emphasizing ease of use, automation, and integration with cloud-native data infrastructure. The company served data-driven organizations looking to improve data discovery, governance, and collaboration across their teams.

Products & Features

Data Catalog

Automated data discovery and cataloging across the modern data stack

Data Lineage

Automated tracking of data flow and transformations across systems

Metadata Management

Centralized metadata collection and management from multiple data sources

Collaboration Tools

Features enabling data teams to document, discuss, and share knowledge about data assets

Key Features
Automated metadata extractionColumn-level lineage trackingIntegration with modern data stack toolsCollaborative documentationSearch and discoveryData quality insights
Use Cases
Data discovery and explorationImpact analysis for data changesData governance and complianceOnboarding new data team membersUnderstanding data dependenciesImproving data quality
Customer Segments
Data-driven enterprisesTechnology companiesFinancial servicesE-commerce companiesOrganizations with modern data stacks
Corporate history
  • 2020Founded
Connections

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