Scale
Supercharge Databricks Performance with Kyvos
This document demonstrates how Kyvos can deliver up to 10x faster query performance and 15x better cost efficiency when compared to native Databricks performance. With Kyvos semantic layer on top of Databricks, enterprises get instant, scalable analytics for thousands of concurrent users while drastically reducing compute consumption and query costs.
The combined stack maximizes the power of Databricks’ lakehouse architecture while eliminating the latency and cost barriers of direct SQL-based querying. Organizations can achieve equal analytical output with up to 90% fewer analyst hours, boosting productivity and driving immediate ROI.
What You Gain with Kyvos on Databricks
Query Costs Reduced by 15x
Run enterprise-grade analytics on Databricks without the hefty per-query price tag.
10x Faster Query Performance
Sub-second dashboard responses at any scale, regardless of data volume or concurrency.
Zero Repeated Compute
Data is read once and results reused, eliminating redundant Databricks scans across every query.
Effortless Scaling
Query engines spin down when idle, so cloud costs scale with usage — not data growth.
A Quick Reckoner
| Speed | Databricks | Databricks with Kyvos |
|---|---|---|
| Average Query Time (1.2B rows) | 11.61 sec | 1.19 sec |
| Query Push-Down | Sends requests to the underlying table every time | Reads data only once from the source |
| Query Type | Direct SQL on raw tables | Served from smart aggregates |
| Performance Consistency | Variable, depends on compute/resources | Consistently fast |
| Dashboard Experience | Slows down | Sub-second responses |
Get the Highlights
