SQream vs Collibra
Side-by-side comparison of AI visibility scores, market position, and capabilities
SQream uses NVIDIA GPU acceleration for SQL analytics on massive datasets; raised $45M Series C (Sep 2023); new CEO Liam Galin appointed Apr 2025; showcased GPU analytics at NVIDIA GTC 2025; serves finance, telecom, and healthcare.
About
SQream (also known as SQream Technologies) is a Tel Aviv-based data analytics company founded in 2010 that has built a SQL database and analytics platform powered by NVIDIA GPU acceleration. The company''s core premise is that traditional CPU-based data warehouses are fundamentally limited in their ability to process the massive dataset sizes required for modern AI, machine learning, and analytics workloads — and that GPU parallelism can deliver orders-of-magnitude improvements in query performance, data ingestion speed, and cost-efficiency at scale.
Collibra is a leading data intelligence platform providing enterprise data catalog, governance, lineage, and quality capabilities for regulated and data-driven organizations.
About
Collibra is a data intelligence platform that provides enterprise organizations with a unified environment for data catalog, data governance, data lineage, and data quality management — covering the full lifecycle of data trust from asset discovery and documentation through policy enforcement and compliance reporting. The platform's data catalog provides a searchable inventory of data assets enriched with business context — business glossary terms, data classifications, ownership assignments, and stewardship workflows — that allows data consumers to find, understand, and trust data before using it in analytics, reporting, or decision-making. Collibra's governance framework enables organizations to define data policies, assign stewardship responsibilities, manage data requests through structured workflows, and track policy compliance across the data landscape — critical capabilities for regulated industries where data handling must be documented and auditable.
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