---
title: "The data lakehouse is a better data warehouse: 2026 benchmarks and proof"
description: "Data warehouses have been the standard for structured SQL analytics for two decades but cannot serve modern AI, ML, streaming, and unstructured data workloads. The data lakehouse now matches warehouse SQL performance while serving all these workloads from a single governed foundation. Databricks Lakehouse improved production SQL workload performance by 77% from a 2022 baseline, with BI queries improving 14% over a recent five-month period. Customer migrations show 90% faster queries and 30–40% cost reduction at Lumen Technologies, and 80–90% faster analytics at Trek Bicycle. The lakehouse eliminates redundant data copies, supports open formats like Delta Lake and Iceberg, and extends governance to AI agents through Unity Catalog and Unity Gateway."
---

# The data lakehouse is a better data warehouse: 2026 benchmarks and proof

[Databricks](https://yomu.fyi/company/databricks) · Joanna Zouhour · Oct 12, 2026

**Type:** Problem & solution

## Summary

Data warehouses have been the standard for structured SQL analytics for two decades but cannot serve modern AI, ML, streaming, and unstructured data workloads. The data lakehouse now matches warehouse SQL performance while serving all these workloads from a single governed foundation. Databricks Lakehouse improved production SQL workload performance by 77% from a 2022 baseline, with BI queries improving 14% over a recent five-month period. Customer migrations show 90% faster queries and 30–40% cost reduction at Lumen Technologies, and 80–90% faster analytics at Trek Bicycle. The lakehouse eliminates redundant data copies, supports open formats like Delta Lake and Iceberg, and extends governance to AI agents through Unity Catalog and Unity Gateway.

## Context

Data warehouses have been the standard for structured SQL analytics for two decades, but they cannot serve modern workloads like AI agents, ML, streaming, and unstructured data. The lakehouse is proposed as a unified platform that matches warehouse SQL performance while supporting all these workloads.

## Approach / What changed

The solution is the Databricks Lakehouse, which uses the Photon vectorized execution engine, predictive optimization, and concurrency management to match warehouse SQL performance. It adds Lakehouse//RT for real-time analytics, Unity Catalog and Unity Gateway for data and AI governance, and open table formats (Delta Lake and Iceberg) to eliminate data copying. For migration, the post recommends quantifying hidden costs, running a side-by-side proof of concept, starting with new workloads, using Lakebridge for migration assessment, and setting explicit migration gates.

## Takeaways

- Databricks Lakehouse improved production SQL workload performance by 77% from a 2022 baseline, equivalent to roughly a 4x improvement on the Databricks Performance Index.
- Customer migrations from warehouses to lakehouses show 25–75% cost reductions, with AXA Japan reducing warehouse costs by 60% and Lumen Technologies cutting compute costs by 30–40%.
- The lakehouse eliminates data copying by serving SQL queries, Spark transformations, streaming pipelines, Python notebooks, and ML training from the same Delta Lake or Iceberg tables, reducing storage and governance overhead.

## FAQ

### Is the lakehouse faster than a warehouse for SQL?

For most workloads, the lakehouse now matches or exceeds the performance of warehouses for SQL. Databricks Lakehouse has improved 77% since 2022, and independent TPC-DS testing shows sub-second p50 latency on 1-TB workloads at 74% lower cost. The warehouse may still edge ahead on highly concurrent short queries with warm caches, but the gap is narrow and closing.

### How much can I save by migrating?

Published customer results range from 25% to 75% cost reduction. AXA Japan reduced warehouse costs by 60%. The savings come from eliminating redundant systems and data copies, not just cheaper queries.

### How long does a migration take?

It depends on complexity, but timelines have compressed. Vivriti Capital migrated from Redshift in about 8 weeks. IndusInd Bank migrated 1.5 PB across 44 business areas in 15 months. Lakebridge and the Agentic Code Converter automate assessment and translation to accelerate the process.

**Tags:** [AI Agents](https://yomu.fyi/topic/ai-agents), [Apache Iceberg](https://yomu.fyi/topic/apache-iceberg), [Data Lakehouse](https://yomu.fyi/topic/data-lakehouse), [Data Warehousing](https://yomu.fyi/topic/data-warehousing), [Delta Lake](https://yomu.fyi/topic/delta-lake)

- Source: [Databricks](https://www.databricks.com/blog/data-lakehouse-better-data-warehouse-2026-benchmarks-and-proof)
- Source URL: https://www.databricks.com/blog/data-lakehouse-better-data-warehouse-2026-benchmarks-and-proof
- Ingested by Yomu: 2026-10-12T21:00:13.181Z

[Read original post](https://www.databricks.com/blog/data-lakehouse-better-data-warehouse-2026-benchmarks-and-proof)