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Developer Experience
Query everything, scale and secure fast on your own stack
Run SQL + AI workloads that auto scale, block bad jobs, run vector search, and stay secure with row/column masking—no tuning, no trust issues.
SQL meets AI, right in your lakehouse
Query structured and unstructured data with cosine similarity. No vector DBs. Just pure vector search.
Auto-scaling that adapts to query load
Set min and max, we handle the rest. Executors scale with load with no latency spikes, no job failures, no manual tuning.
Guardrails to stop “bad” queries early
Set thresholds per cluster. Log, alert, or cancel in real time before bad queries waste compute.
Sub-second streaming of data in your lake
No Flink, no ETL, no learning curve. Stream directly to your lakehouse, query with sub-second latency using SQL/Python.
Enterprise-grade security and governance
Row/column-level control, IAM integration, and audit-ready logs. SOC 2, ISO, HIPAA, and GDPR—secure by design, with no slowdown.
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Use Cases
Run your most resource-intensive SQL and AI workloads
Get predictable SLAs, instant query responses, and radically lower compute costs-all with no query rewrites or app changes.
Packaged Analytics
Deliver embedded, multi-tenant analytics seamlessly within your SaaS applications. Gain 10x faster performance at scale while reducing infrastructure costs by up to 60% and operational complexity.
Interactive Analytics
Enable real-time dashboards and dynamic data exploration at massive scale. Deliver sub-2-second response times for 1000+ QPS with consistent SLAs and UX and without any latency.
Ad-hoc Analytics
Run complex ad-hoc queries 10x faster across diverse data sources (object storage, OLAP, data streams, and more) from a unified engine. Achieve zero-failed SLAs due to poorly optimized queries and resource constraints.
Scheduled Analytics
Run frequent, high-volume scheduled analytics with 99.99% reliability for scheduled workflows—without downtime, data delays, or compute cost overruns, even with rapid refresh cycles.
Real Time Ingest
Stream data into your lakehouse with sub-second latency. Skip Flink, ETL, and pipeline overhead. Query fresh events instantly using SQL or Python—no shuffle, no joins, no delay between ingestion and analysis.
Vector Search
Run semantic search on unstructured data using built-in cosine similarity. No vector DBs, no retrieval pipelines. Query text like structured rows with SQL—fast, scalable, and lakehouse-native for instant, AI-powered insights.
Packaged Analytics
Deliver embedded, multi-tenant analytics seamlessly within your SaaS applications. Gain 10x faster performance at scale while reducing infrastructure costs by up to 60% and operational complexity.
Interactive Analytics
Enable real-time dashboards and dynamic data exploration at massive scale. Deliver sub-2-second response times for 1000+ QPS with consistent SLAs and UX and without any latency.
Ad-hoc Analytics
Run complex ad-hoc queries 10x faster across diverse data sources (object storage, OLAP, data streams, and more) from a unified engine. Achieve zero-failed SLAs due to poorly optimized queries and resource constraints.
Scheduled Analytics
Run frequent, high-volume scheduled analytics with 99.99% reliability for scheduled workflows—without downtime, data delays, or compute cost overruns, even with rapid refresh cycles.
Real Time Ingest
Stream data into your lakehouse with sub-second latency. Skip Flink, ETL, and pipeline overhead. Query fresh events instantly using SQL or Python—no shuffle, no joins, no delay between ingestion and analysis.
Vector Search
Run semantic search on unstructured data using built-in cosine similarity. No vector DBs, no retrieval pipelines. Query text like structured rows with SQL—fast, scalable, and lakehouse-native for instant, AI-powered insights.
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