Striim
Striim is a real-time streaming data integration and validation for enterprise analytics pipelines.
Striim operates in the Unclassified segment.
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- Founded
- 2012
- Headquarters
- United States
- Core Segment
- Unclassified
- Company Size
- 50–200
- Official Links
- Website
- Verified
- 2026-03-12
Key insights about Striim
Subsidiaries
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Competitors
Key competitors include Fivetran, Hevo.
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Striim: About
The company operates a B2B software model focused on real-time data integration and streaming analytics infrastructure. It creates value by enabling enterprises to capture database changes via log-based CDC, transform and route data in motion and feed data warehouses and analytics systems in near real time, reducing latency and operational overhead versus batch ETL. The core offerings are a self-managed platform deployable on-premise or in customers’ own clouds, and a fully managed SaaS edition on major public clouds, both exposing similar streaming and connector capabilities. Additional value is provided through specialised validation and reconciliation tooling that reduces data quality risks, and embedded AI assistance that lowers operational complexity. Revenue is primarily derived from recurring software and SaaS contracts with enterprises, often accompanied by implementation and support services.
Striim: Market Position
Striim, Inc. is a US-based data infrastructure company providing real-time data integration and streaming platforms. Its products enable log-based change data capture (CDC), continuous data pipelines and low-latency analytics across on-premise and cloud environments, with a focus on ingesting, processing and delivering data into data warehouses and analytics platforms such as Google BigQuery.
The company generates revenue by selling a mix of managed cloud services and self-managed software licences, supplemented by enterprise support and professional services. Its customers are primarily enterprise and mid-market data engineering and IT teams that require reliable, mission-critical streaming data integration, data validation and operational tooling, rather than consumers or small casual users.
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