Working with Analytical Data

Vendia’s MCPaaS enables data engineers, data analysts and AI Ops to connect to and query remote data lakehouses and manage that data on Vendia for seamless distribution with partners or AI applications or workflows.

Vendia’s cross-warehouse/lakehouse analytical data management capability seamlessly bridges the gap between on-premises and cloud data warehouses/lakehouses, reducing storage costs and simplifying data integrations across cloud, on-premises, and BI tools for enterprise AI outcomes.

Key Capabilities

• MCP Tools integration: Ability to read/query Iceberg tables in Vendia
• Multi-platform ingestion: Ingest data from popular sources like Snowflake, Cloudera CDP Hive, MySQL-compatible databases, PostgreSQL-compatible databases, Google BigQuery, Databricks, Amazon S3, and CSV Browser Upload (more coming soon)
• Data transformation: Apply filtering, masking, and joins to create the datasets you need
• Flexible sharing: Distribute via shared tables or export as Apache Iceberg, Delta Share, or CSV
• Governance: Role-based access controls with full audit trails and data lineage
• No infrastructure: Point-and-click sharing without provisioning or managing infrastructure

How It Works

1. Connect your data sources
2. Optionally transform and prepare your data
3. Choose sharing method (collaborative tables or data product exports)
4. Invite partners and manage access controls

For detailed information, see our Getting Started Guide and FAQ.

Questions? Contact Vendia Support.