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Cloud Cost Optimization

Reduce analytics costs on cloud without compromising on your business needs

High Scalability

Enable analysis on years of history without worrying about cloud costs.

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Elasticity

Auto scaling to optimize costs. Scale down to save costs during off-hours.

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OPTIMIZED costs

Create once, query multiple times approach for cloud cost optimization.

High Performance on Every Data Platform

CREATE ONCE, QUERY MULTIPLE TIMES APPROACH

Scale limitlessly without any significant impact on your costs. You can add any number of users and let them fire as many queries as they need. Our powerful preaggregation engine reduces querying costs substantially, irrespective of data size or query complexity.

AUTO-SCALING FEATURE

Scale analytics up and down to deliver consistent performance during spikes and reduce resource consumption during lean periods. Our auto-scaling feature helps you pre-schedule querying activities in response to predictable load changes, reducing your costs further.

CLOUD-NATIVE ARCHITECTURE

Designed to leverage the native elasticity and cheap cloud storage for both creating aggregates and querying, Kyvos helps you scale cost-effectively. Advanced algorithms ensure optimal utilization of resources while creating aggregates, even on massive datasets.

Kyvos + Databricks: The Powerful Duo for Fastest Analytics on the Cloud at Lowest Costs

The combined power of Kyvos and Databricks enables sub-second query responses on trillions of rows of data stored on the cloud while ensuring optimal utilization of cloud resources.

How to Achieve Snowflake Cost Optimization while Supercharging Analytics Performance

As data explodes and usage increases, your compute costs can rise significantly leading to unpredictable bills. Learn how Kyvos helps reduce your Snowflake costs while delivering exceptionally high query performance.

Resources

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Whitepaper

Analytics on the Cloud: Think Big with Modern OLAP

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Datasheet

High-performance Analytics at Massive Scale on Cloud

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Blog

Maximizing the Benefits of Cloud Analytics with Scheduled Cluster Scaling

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