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Brief
Stemma was acquired by Teradata.
Stemma

Stemma

Data Infrastructurestemma.ai

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.

Last updated May 11, 2026 by ATDb automated enrichment

Founded
2020
HQ
San Francisco, California, United States
Parent
Connections
5

At a glance

Employees
11-50
Funding
$4.8M
4integrations1corporate family

About

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

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.

Business model

SaaS

Target market

Mid-Market, Enterprise

What they offer

  • 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

Tech & specs

Technology stack

Cloud-native architectureIntegration APIs for data sourcesMetadata extraction enginesGraph databases for lineage

Security & compliance

SOC 2GDPR

Deployment

Cloud

API

Yes

Corporate history
  • 2020Founded
Connection details

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