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Databricks Lakehouse

Databricks Lakehouse Architecture unifies data, analytics, and AI by combining elements of data lakes and data warehouses.

Venture Funded$3.5B+Series HAndreessen HorowitzBattery VenturesMicrosoft

data engineeringdata governancescalable analyticscloud-native

About

The Databricks Data + AI Platform is built on lakehouse architecture, which integrates data lakes and data warehouses to reduce costs and accelerate data and AI initiatives. The vendor states that this architecture is unified, open, and scalable. It offers one architecture for integration, storage, processing, governance, sharing, analytics, and AI, supporting both structured and unstructured data. The platform is built on open source projects like Apache Spark, Delta Lake, and MLflow, and uses Delta Sharing for secure data sharing without replication. Databricks states that the platform provides automatic optimization for performance and storage, aiming for the lowest total cost of ownership and high performance for data warehousing and AI use cases, including large language models.

Read from databricks.com on 2026-08-26. We describe what the vendor states; we do not audit it.

Enterprise Readiness

from cataloged data

65/100 · Strong

Security & ComplianceNot disclosed

No compliance certifications listed

Deployment FlexibilityStrong

Flexible deployment: Cloud, Hybrid

Integration DepthStrong

8 documented integrations

Proven AdoptionPartial

5 documented use cases

Company MaturityStrong

Founded 2013 · Series H

Composite of public compliance, deployment, integration, adoption, and company signals. “Not disclosed” reflects gaps in available data, not a vendor deficiency.

Independently sourced

Pulled directly from regulator filings and platform APIs. No vendor or editorial input.

Activity classifier

Active

last GitHub commit 0d ago

GitHub API2026-05-27

databricks

SDK / client libraries· active 3mo ago

Python · TypeScript · Scala · Go

Enterprise Use Cases

ETL and data ingestion pipelines

Real-time analytics and reporting

Machine learning model development

Data governance and compliance

Data warehousing modernization

Integrations

Apache SparkDelta LakeMLflowAWSAzureGoogle CloudTableauPower BI

How Databricks Lakehouse compares

Tool	Readiness	Pricing	Deployment	Compliance	Integrations
Databricks Lakehouse	65 · Strong	Enterprise	Cloud, Hybrid	—	8
Airbyte	Not scored	Freemium	Cloud, On-Premise, Hybrid, Self-Hosted	—	8
Astronomer Astro	70 · Strong	Enterprise	Cloud, On-Premise, Hybrid, Self-Hosted	—	8
Elastic AI	70 · Strong	Enterprise	Cloud, On-Premise, Hybrid, Self-Hosted	—	8

Peers from the same category, ranked by Enterprise Readiness. Readiness is a composite of cataloged compliance, deployment, integration, adoption, and company signals.

Frequently Asked Questions

What is Databricks Lakehouse used for?

Databricks Lakehouse is databricks Lakehouse Architecture unifies data, analytics, and AI by combining elements of data lakes and data warehouses. It is commonly used for etl and data ingestion pipelines, real-time analytics and reporting, machine learning model development, and data governance and compliance.

Is Databricks Lakehouse free, and how is it priced?

Databricks Lakehouse uses enterprise pricing, typically a custom quote based on seats, usage, and requirements. Contact the vendor for a quote.

How can Databricks Lakehouse be deployed?

Databricks Lakehouse supports Cloud and Hybrid deployment. It is delivered as a cloud-hosted service.

What does Databricks Lakehouse integrate with?

Databricks Lakehouse documents 8 integrations, including Apache Spark, Delta Lake, MLflow, AWS, Azure, and Google Cloud.

When was Databricks Lakehouse founded?

Databricks Lakehouse was founded in 2013 and has raised $3.5B+ in funding.

Is Databricks Lakehouse enterprise-ready?

Based on cataloged data, Databricks Lakehouse has an Enterprise Readiness score of 65/100 (Strong tier), derived from its compliance, deployment, integration, adoption, and company-maturity signals.

Quick Facts

PricingEnterprise

DeploymentCloud, Hybrid

Founded2013

Funding$3.5B+

CategoryData & MLOps

Procurement

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