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What is the Databricks Data Intelligence Platform?

The Databricks Data Intelligence Platform is a unified, open platform that combines data engineering, analytics, and AI. Built on the lakehouse architecture, it enables organizations to manage all their data, analytics, and AI assets in one place, ensuring governance, scalability, and performance.

Enable Customer-Facing Analytics on Databricks

CelerData Cloud, powered by StarRocks, brings high-concurrency, sub-second analytical queries directly to your Databricks Data Intelligence Platform—without ETL or data duplication. Run product dashboards, embedded reports, or AI-driven experiences on live, governed lakehouse tables and deliver data-warehouse performance without the governance headache.

Real-time, sub-second queries

Engineered for consistently delivering millisecond-level response times even when tens of thousands of queries arrive per second.

Effortless scalability

Scale your CelerData compute warehouses in minutes—no repartitioning or data movement—while maintaining consistent sub-second SLAs at any concurrency.

Unified governance across all data and AI assets

Governed by Unity Catalog—ensuring consistent access control, lineage, and auditing alongside all your models, features, and datasets in a single governed platform.

Customer-Facing Analytics Use Cases

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Pinterest

With over 500 million monthly users, Pinterest uses real-time analytics to help advertisers optimize campaigns and improve engagement. Learn how Pinterest handles its growing data needs, providing faster, more impactful insights.
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Demandbase

As a leading B2B marketing platform, Demandbase delivers analytics directly to enterprise customers through embedded dashboards. By switching from ClickHouse to StarRocks, they eliminated complex denormalized pipelines, enabling governed, real-time insights with significantly lower operational overhead.
See Use Case
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TRM Labs

TRM Labs equips investigators with tools to detect crypto-related crimes. To support their petabyte-scale, customer-facing analytics workloads, they built a lakehouse using Apache Iceberg and StarRocks—enabling sub-second, high-concurrency queries in both cloud and on-prem environments.
See Use Case

How CelerData Enhances Databricks

Vectorized C++ execution engine

CelerData’s fully SIMD-optimized engine scans, filters, joins, and aggregates in columnar batches, delivering consistent sub-second latency even at tens of thousands of QPS.

Unified governance with Unity Catalog

CelerData natively integrates with Unity Catalog to enforce fine-grained permissions, trace data lineage, and align analytics with AI models, features, and business metrics—all from a single, governed source.

Elastic, multi-warehouse compute

Deploy multiple scalable and isolated compute warehouses to scale linearly with traffic. Each workload stays performant and secure, whether it’s powering end-user reports or internal data apps.

Auto Materialized Views (AutoMV)

Seamlessly boost performance and reduces cost by recommending impactful materialized views automatically rewriting queries behind the scenes.