Databricks Data Intelligence Platform vs Alation

by Gralio Apr 29, 2025

Databricks Data Intelligence Platform and Alation serve different core purposes in the data landscape. Databricks provides a comprehensive environment for processing data, running analytics, and building AI models, essentially the workshop for data tasks. Alation acts as the intelligent map and library for your data, focusing on helping users find, understand, govern, and trust data assets across the organization.

At Gralio.ai we help to simplify your decision-making process by offering detailed, side-by-side software comparisons like this one, to help you confidently choose the tool that aligns with your business goals.

This comparison was created by analysing 384 reviews and 60 websites, saving 2 hours, 38 minutes of reading.

Logo of Databricks Data Intelligence Platform
Logo of Alation

About

Databricks Data Intelligence Platform is a cloud-based platform designed to help mid-size to large businesses manage and analyze data. It offers a range of tools for data warehousing, data engineering, data science, and machine learning, all in one place. Databricks aims to simplify data processes, reduce costs, and enable companies to build and deploy AI solutions. They are well-known for their work with open-source technologies, making them a popular choice for businesses invested in those ecosystems.
Alation is a data intelligence platform that helps you understand and manage your company's data. It's like a map for your data, showing you what you have, where it lives, and how it's used. This helps your team find the right data for projects, ensures data quality and compliance, and can even help build AI models you can trust. Alation is used by many large companies and integrates with many data tools you may already be using.

Summary

Main difference
Databricks offers a unified platform with integrated tools for doing data work (processing, analyzing, building models) on its lakehouse architecture. Alation focuses on understanding and managing data by providing a dedicated data catalog with strong governance, discovery, and collaboration features that connects to various data sources.

Relative strengths of Databricks Data Intelligence Platform (compared to Alation)

  • Unified Data Processing & AI: Databricks combines tools for data warehousing, data engineering, data science, and AI development in a single platform, allowing teams to manage the entire data lifecycle from ingestion to model deployment without switching tools, which Alation does not offer.

  • Powerful Analytics Engine: It incorporates advanced features like serverless SQL warehouses and Spark integration (e.g., Pandas Spark API) for high-performance querying and processing of large datasets directly within the platform.

  • Lakehouse Foundation: Built on an open lakehouse architecture, it efficiently manages both structured and unstructured data together, offering flexibility for diverse analytics and AI use cases beyond the scope of a traditional data catalog like Alation.

Relative weaknesses of Databricks Data Intelligence Platform (compared to Alation)

  • Data Discovery & Understanding Focus: Alation provides a more specialized and user-friendly interface focused purely on data cataloging, search, and collaboration, often cited by users as easier for non-technical staff to find and understand data compared to navigating Databricks' broader platform.

  • Implementation Complexity & Cost Concerns: Databricks has reports of difficult implementation ("highly negative" rating) and potentially less transparent pricing ("highly negative" rating), which can be significant hurdles for mid-sized businesses prioritizing value and ease of setup, compared to Alation's noted strong support and onboarding.

  • Dedicated Governance Features: While Databricks has Unity Catalog for governance, Alation specializes in active metadata management and weaving governance workflows directly into the data discovery process, potentially offering more mature or granular features for data stewardship and compliance documentation.

Who should use Databricks Data Intelligence Platform VS. Alation

We see Databricks as a strong contender for mid-sized to large companies wanting to bring their data and AI efforts under one roof. It's a unified platform built on a lakehouse architecture, covering everything from data warehousing to machine learning. Users often praise features like the serverless SQL warehouse and Unity Catalog for governance, though some find cluster startup times slow. It's particularly appealing if your organization leverages open-source tech for data tasks and aims to simplify complex data pipelines and AI deployment effectively across teams

Alation is a data intelligence platform designed to help companies make sense of their data. We notice users often praise its user-friendly interface for finding and understanding data easily. It's particularly helpful for businesses looking to improve data governance, manage data quality, and build trustworthy AI models. While some find the initial setup challenging, many appreciate its collaborative features and robust search capabilities for navigating complex data landscapes

  • In our experience, Databricks is an excellent fit for medium-sized companies and large enterprises looking to consolidate their data operations.

  • While built for businesses across all sectors, we find Databricks particularly popular within the Software, IT, and Telecommunications industries.

  • Based on our observations, Alation works well for medium-sized businesses, but it truly shines in large enterprises with complex data needs.

  • In our experience, Alation is quite versatile and proves valuable across many industries, especially those dealing with large volumes of data.

Databricks Data Intelligence Platform and Alation features

Supported
Partially supported
Not supported
Type in the name of the feature or in your own words tell us what you need

  • Lakehouse architecture
    Supported

    Databricks Data Intelligence Platform is built on a lakehouse architecture.

    Partially supported

    Alation supports lakehouse architecture through integration with Databricks, enhancing governance and collaboration.

  • Simplified data and AI acceleration
    Supported

    Databricks simplifies and accelerates data and AI initiatives, from ETL to warehousing and generative AI.

    Partially supported

    Alation accelerates data and AI goals by ensuring trusted and compliant AI initiatives.

  • Embedded Data Governance
    Supported

    Databricks supports data governance through features like Unity Catalog.

    Supported

    Alation supports embedded data governance through automated policy enforcement, contextual guidance, and integrated stewardship tools.

  • Data Warehouse Integration
    Supported

    Databricks Data Intelligence Platform is highly capable of integrating with other warehouse databases.

    Supported

    Alation integrates with popular data warehouses like Snowflake, Redshift, and BigQuery.

  • Data Governance Tool Integration
    Supported

    Databricks Data Intelligence Platform supports integration with data governance tools, such as Immuta.

    Supported

    Alation integrates with data governance tools like Snowflake Horizon and supports open data quality initiatives.

  • Data Source Integration
    Supported

    Databricks Data Intelligence Platform offers extensive options for integrating with external data sources, including built-in connectors, driver support, and integrations with BI and ETL tools.

    Supported

    Alation integrates with external data sources using pre-built and custom connectors.

Qualities

  • Value and Pricing Transparency
    +0.08
    Neutral sentiment
    No data
  • Customer Service
    +1
    Strongly positive sentiment
    No data
  • Ease of Use
    +0.84
    Strongly positive sentiment
    No data
  • Reliability and Performance
    +0.77
    Strongly positive sentiment
    No data
  • Ease of Implementation
    +0.27
    Neutral sentiment
    No data
  • Scalability
    +1
    Strongly positive sentiment
    No data

Databricks Data Intelligence Platform and Alation Pricing

No data

User sentiment

Neutral
+0.08

See full Pricing page

No data

See full Pricing page

Databricks Data Intelligence Platform and Alation review insights

384 reviews analysed from

Users love

  • The Databricks SQL warehouse serverless feature is excellent.
  • Unity Catalog improves data governance and accessibility.
  • Lakehouse flow monitoring provides helpful insights into data processes.
  • Pandas Spark API allows for easy distributed computing with Python.
  • User-friendly interface simplifies data discovery and access.
  • Robust search capabilities empower quick information retrieval.
  • Collaborative features foster effective communication and knowledge sharing.
  • Flexible and adaptable for organizations of all sizes.
  • Excellent customer support and onboarding experience.

Users dislike

  • Cluster startup times are slow.
  • Documentation could be improved with more examples.
  • AI assistant needs improvement, especially for complex SQL queries and errors.
  • Occasional unplanned downtime can be disruptive.
  • Difficult setup and configuration, especially for data governance policies and external tool integrations.
  • Overwhelming documentation and navigation, making it hard to find specific information or troubleshoot.
  • Limited lineage capabilities, though improvements are planned.
  • Backend not user-friendly, requiring research for some tasks.
  • Limited data quality capabilities built-in.

Databricks Data Intelligence Platform and Alation Ratings

  • G2
    4.5/5
    (319)
  • Glassdoor
    4.3/5
    (1199)
  • G2
    4.4/5
    (65)
  • Glassdoor
    3.6/5
    (219)

Company health

Employee growth

27% increase in the last year
13% decrease in the last year

Web traffic

7% increase in the last quarter
1% decrease in the last quarter

Financing

August 2024 - $19B
January 2023 - $315M

How do Databricks' open-source features compare to Alation's data governance focus?

Databricks heavily leverages open-source technologies like Spark and Delta Lake as core components of its unified platform, providing tools for data engineering, science, and warehousing within this open framework; its governance features, like Unity Catalog, support this broad, open architecture. Alation, conversely, specializes primarily in data governance, cataloging, and discovery as its central function, focusing on helping users find, understand, and trust data across various systems, rather than emphasizing its own open-source foundations.

Which platform better supports building and deploying trusted AI models?

Alation appears better suited for building and deploying trusted AI models, as it explicitly lists features designed to ensure data quality, transparency, compliance, and lineage tracking specifically for AI development. It emphasizes documenting insights and collaboration for ethical AI. While Databricks provides a comprehensive platform for building and deploying AI solutions and includes data governance features like Unity Catalog, its core description focuses more broadly on the data and AI lifecycle rather than specifically highlighting the trust, transparency, and compliance aspects critical for trusted AI as Alation does.

What are the advantages of Databricks Data Intelligence Platform?

Databricks Data Intelligence Platform offers a unified environment combining data warehousing, engineering, science, and machine learning on a lakehouse architecture, simplifying data processes and fostering collaboration across the organization. It features a Data Intelligence Engine designed to understand data uniqueness for tailored analysis and is noted for its strength in open-source ecosystems. Users particularly appreciate features like the SQL warehouse serverless capability, Unity Catalog for enhanced data governance and accessibility, lakehouse flow monitoring, and the Pandas Spark API for distributed Python computing. The platform generally receives positive feedback regarding ease of use, reliability, performance, scalability, and customer service, alongside positive company growth indicators.

What are the disadvantages of Databricks Data Intelligence Platform?

Based on the provided information, Databricks Data Intelligence Platform has several disadvantages. Users report highly negative experiences regarding value and pricing transparency, as well as the ease of implementation. Practical drawbacks include slow cluster startup times, documentation that lacks sufficient examples, and an AI assistant that needs improvement, especially for complex SQL queries and error handling. Furthermore, occasional unplanned downtime can be disruptive to operations.

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Page co-authored by
MK
Michal Kaczor
CEO at Gralio

Michal has worked at startups for many years and writes about topics relating to software selection and IT management. As a former consultant for Bain, a business advisory company, he also knows how to understand needs of any business and find solutions to its problems.

TT
Tymon Terlikiewicz
CTO at Gralio

Tymon is a seasoned CTO who loves finding the perfect tools for any task. He recently headed up the tech department at Batmaid, a well-known Swiss company, where he managed about 60 software purchases, including CX, HR, Payroll, Marketing automation and various developer tools.

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