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Challenges

High costs driven by heavy compute in data warehouses and Spark batch jobs — with costs rising as data grows by 17 billion records every month.

1 Trillion

Warehouse Storage

40B

Warehouse MV

1B

Relevant Query Output

24h

SLA

Impacts

0.8B

Warehouse Storage

0.8B

Warehouse MV

0.8B

Relevant Query Output

6h

SLA

Breakthrough

94%

Aggregation Efficiency

Streaming

Minimized Workload

Orchestration

Scaling on Data Volume

Lakehouse

Unified Catalog

Wrap-up

We love technology that’s been proven in real production. Scalor.AI strikes the right balance between cost, latency, performance, and stability — and among them, stability matters most. Because in production, failure is not an option.

All metrics are based on verified production workloads unless otherwise stated.