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DataHub

Free plan Open source APILinuxMacSelf-hostedWebWindows

Visit DataHub Alternatives Pricing

DataHub's own site

What DataHub is

DataHub brings technical metadata, business knowledge, and documentation together for enterprise data and AI agents. It is available as self-hosted DataHub Core or managed DataHub Cloud. Cloud offers natural-language search, an Ask DataHub chat agent, smart ranking, and a hosted MCP server for connecting AI tools to the catalog. It also supports automated schema, freshness, volume, and custom quality checks, AI anomaly detection, and incident workflows. Its cross-platform, column-level lineage follows data from source through transformations and AI models to downstream assets. DataHub Cloud has more than 100 pre-built connectors, with native integrations including Slack, Microsoft Teams, Chrome, and BI tools. The maker describes Cloud as SOC 2 compliant, with role-based and attribute-based access controls and an in-VPC remote execution option for sensitive sources. Cloud availability is described as SLA-backed at 99.5%, with onboarding and dedicated customer support. Core is free to deploy, but users manage installation and operations themselves; Cloud pricing depends on data volume, users, and capabilities. A Google Cloud offer advertises a 21-day Cloud trial.

Who it suits

DataHub may suit enterprise data teams that need metadata discovery, lineage, and data quality workflows. Choose between self-managed Core and managed Cloud based on operational needs and Cloud pricing scope.

What it does well

  • Free, self-hosted Core option.
  • Cloud includes more than 100 pre-built connectors.
  • Column-level lineage spans sources and downstream assets.
  • Cloud offers automated checks and anomaly detection.
  • Cloud trial is advertised for 21 days.

What to know first

  • Core requires users to manage installation and operations.
  • Core lacks SSO and fine-grained permissions out of the box.
  • Cloud pricing depends on data volume, users, and capabilities.

Limits

DataHub Core is free to deploy, but it has basic access controls and no SSO or fine-grained permissions out of the box. Core users handle installation, configuration, upgrades, uptime, and troubleshooting. Cloud pricing depends on data volume, users, and selected capabilities.

Plans

PlanBilled and limitsPrice
DataHub Coreopen source · self-hosted · core discovery, lineage, observability and governanceFree
DataHub Cloudmanaged SaaS · pricing varies by data volume, users and capabilities · 99.5% SLAOn request

As datahub.com lists them, read 14 Oct 2026. The maker's own page has the final word.

Getting started

  1. Visit datahub.com.
  2. Choose DataHub Core for self-hosting or DataHub Cloud for managed service.
  3. For Core, deploy the free open-source plan and handle installation and configuration.
  4. For Cloud, contact sales to scope pricing to your data volume, users, and capabilities.
  5. Use the Google Cloud offer page to access its advertised 21-day Cloud trial with a dedicated instance and full platform access.

DataHub brings together metadata discovery, a business glossary, lineage and data observability for enterprise data teams. It is best suited to organisations that need to connect data assets with business context and AI tools, and can either operate an open-source deployment or pay for a managed service.

Overview

DataHub frames its platform as a shared context layer for technical metadata, business knowledge and documentation. The combination is useful when teams need to find assets, understand their meaning and follow how they move through data systems and AI models.

Its two deployment choices serve different operating needs. Core is free and self-hosted, but the team is responsible for installation, configuration, upgrades, uptime and troubleshooting. Cloud removes that operational burden in exchange for custom, use-based pricing.

Key features

Discovery and AI connections

DataHub Cloud provides natural-language search, smart ranking and an Ask DataHub chat agent, plus a hosted MCP server that connects AI tools to the catalog. The maker names more than 100 pre-built connectors and native integrations including Slack, Microsoft Teams, Chrome and BI tools. MCP-native integrations include Cortex, Genie, Cursor, Claude, LangChain, Agent Development Kit, CrewAI and custom agents. This breadth makes Cloud a strong fit for teams seeking to put catalog context into existing collaboration, analytics and AI workflows; these discovery features are specifically described for Cloud.

Observability and lineage

Automated checks cover schema, freshness, volume and custom quality rules, with AI anomaly detection and incident workflows for managing issues. Column-level lineage traces data across platforms from source through transformations and AI models to downstream assets. Together, these features help teams investigate how a problem or change could affect dependent data, rather than treating cataloging as a static inventory.

Security and service

Cloud is described as SOC 2 compliant, with role-based and attribute-based access controls and an in-VPC remote execution option for sensitive sources. Data is encrypted at rest and in transit; the company also says it conducts third-party penetration tests and static security analysis. Cloud is fully managed and has SLA-backed 99.5% availability, alongside onboarding, adoption support, a dedicated customer success team and private Slack support. Core instead has basic access controls, community Slack and self-service documentation; it lacks SSO and fine-grained permissions out of the box, a material constraint for organisations with stricter access requirements.

Pricing

DataHub Core

free (billed Free to deploy; open source). Core is self-hosted and includes basic access controls, community support and self-service documentation. It suits teams able to manage their own infrastructure and willing to accept the operational work and more limited access controls. The free price does not include managed uptime, upgrades or dedicated support.

DataHub Cloud

Custom pricing, based on data volume, users and selected capabilities; contact sales. Cloud is managed enterprise SaaS, with pricing scoped to the use case and data environment. A Google Cloud offer advertises a 21-day trial with a dedicated instance and full platform access. The managed operation, stronger access controls and dedicated support may suit teams that cannot take on Core's administration, but the use-based pricing makes it harder to budget without a scoped quote.

Platforms

DataHub supports API access, Linux and web use, as well as self-hosted deployment. Teams can choose between self-managed Core and managed Cloud.

Who it's for

DataHub is a good fit for organisations that need metadata discovery, business context, lineage and observability in one platform, especially where data feeds AI tools and teams need to trace downstream effects. Core is the more natural choice for teams with the capacity to operate open-source software and modest access-control needs. Cloud is better aligned with teams that want managed operations, SLA-backed availability and dedicated support. Core is less suitable when SSO or fine-grained permissions are required out of the box; Cloud may be a poor fit for buyers who need a fixed public price.

Pros and cons

  • Pro: Core is free to deploy, giving technically capable teams a way to run a self-hosted metadata platform without a licence charge.
  • Pro: Column-level lineage, quality checks and incident workflows connect asset discovery with tracing and issue response.
  • Pro: Cloud combines a managed service with more than 100 pre-built connectors, AI discovery features and dedicated customer support.
  • Con: Core requires teams to handle installation, upgrades, uptime and troubleshooting themselves.
  • Con: Core lacks SSO and fine-grained permissions out of the box, limiting its suitability for organisations with demanding access-control requirements.
  • Con: Cloud pricing varies with data volume, users and capabilities, so buyers need a scoped quote to understand cost.

Alternatives

Metadata Management Software is the broader category for comparing tools in this area.

  • Aurelius Atlas is another free, open-source option with self-hosted deployment; choose it if that model is the priority, noting that consulting services are optional and separately priced.
  • Alation Data Intelligence Platform is a paid alternative whose AI capabilities use a pool of consumption units estimated with Alation; consider it if that consumption-unit model fits your buying process.
  • Ab Initio Data Platform is a paid alternative for teams comparing metadata platforms.
  • Dawiso may suit teams seeking published entry pricing: its Standard plan starts at €445 a month and includes five user seats, five contributor licences, 20 viewer licences, unlimited connectors and Slack forum support. It has no free plan.
  • MetaKarta offers a Data Lineage Starter plan at $50 a year, capped at five concurrent users and five pre-selected connectors; consider it if those limits fit a smaller lineage deployment. It has no free plan.
  • Aristotle Metadata Registry is a paid web and API alternative with a Micro plan at $3 a month, including 25 author licences, 125 collaboration licences and 20,000 metadata storage; optional secure hosting is $4 a month.
  • Collibra is another paid, web-based alternative.
  • Progress Semaphore is a paid alternative with a trial and a Development subscription for non-production demos, development and capability evaluations.

Verdict

Choose DataHub if your organisation needs a connected view of metadata, lineage and data quality, particularly to supply context to AI workflows. Core is compelling for teams prepared to run it themselves, while Cloud offers managed operations and stronger support at a custom, usage-based price. Look elsewhere if Core's access controls are insufficient and Cloud's variable pricing does not suit your procurement needs.

Verdict

DataHub combines metadata discovery, lineage, and observability, with a choice of self-hosted or managed deployment. Core is free to deploy; teams considering Cloud should account for use-based pricing and its managed support model.

Questions

Is DataHub free?

DataHub Core is listed as free and is free to deploy. DataHub Cloud pricing depends on data volume, users, and selected capabilities.

Does DataHub offer a free trial?

A Google Cloud offer page advertises a 21-day DataHub Cloud trial with a dedicated instance and full platform access.

Can DataHub be self-hosted?

Yes. DataHub Core is self-hosted, while DataHub Cloud is managed enterprise SaaS.

What integrations does DataHub Cloud offer?

It has more than 100 pre-built connectors and native integrations including Slack, Microsoft Teams, Chrome, and BI tools. Listed MCP-native integrations include Cortex, Genie, Cursor, Claude, LangChain, Agent Development Kit, CrewAI, and custom agents.

What support is included?

Cloud includes onboarding, adoption support, a dedicated customer success team, and a private Slack support channel. Core users get community Slack and self-service documentation.

What access controls are available?

Cloud is described as offering role-based and attribute-based access controls. Core has basic access controls and no SSO or fine-grained permissions out of the box.

Facts from DataHub's own pages

AI integrations
The homepage lists MCP-native integrations with Cortex, Genie, Cursor, Claude, LangChain, Agent Development Kit, CrewAI, and custom agents. · datahub.com, 30 Sept 2026
API
DataHub documents GraphQL and REST interfaces and provides CLI commands for GraphQL operations, search, entity retrieval and metadata changes. · docs.datahub.com, 14 Oct 2026
Availability
DataHub Cloud is fully managed and described as having SLA-backed 99.5% availability. · datahub.com, 30 Sept 2026
Community scale
The project reports more than 16,000 community members, over 750 contributors and adoption by more than 3,000 organizations. · github.com, 14 Oct 2026
Company headquarters
LinkedIn lists the headquarters at 3101 Park Boulevard, Palo Alto, California 94306, United States. · linkedin.com, 14 Oct 2026
Company history
The company page says the founders built DataHub from metadata work at LinkedIn and Airbnb and that the company is headquartered in Palo Alto, California. · datahub.com, 30 Sept 2026
Company origin
DataHub says the commercial company was formed in 2021 as Acryl Data around the LinkedIn-originated open-source project. · datahub.com, 14 Oct 2026
Company size
LinkedIn lists DataHub as a privately held software-development company with 51–200 employees. · linkedin.com, 14 Oct 2026
Compliance
Gartner's product profile states that DataHub Cloud supports SOC II and HIPAA compliance and offers in-VPC execution for sensitive environments. · gartner.com, 14 Oct 2026
Context platform
Its context features ingest metadata into a unified graph, index query history, let experts approve context and expose validated context through MCP, GraphQL, APIs and SDKs. · github.com, 14 Oct 2026
Discovery
The platform provides natural-language search, column-level lineage and profiling for schemas, statistics, ownership and usage. · github.com, 14 Oct 2026
Documentation depth
The documentation site includes integration guides, API and SDK references, deployment, authentication, authorization, developer and release-history sections. · docs.datahub.com, 14 Oct 2026
Extensibility
The project supports custom connectors, transformers, actions and an extensible metadata model. · docs.datahub.com, 14 Oct 2026
Founded
LinkedIn and Gartner list DataHub's founding year as 2021. · linkedin.com, 14 Oct 2026
Funding
Bessemer Venture Partners says it led DataHub's $35 million Series B announced on May 21, 2025, with participation from 8VC, Tru Arrow, SineWave, In-Q-Tel and Zero Prime. · bvp.com, 14 Oct 2026
Governance
DataHub includes a versioned business glossary, ownership and stewardship tools, access policies and compliance controls. · github.com, 14 Oct 2026
Ingestion
The ingestion framework offers scheduled pull connectors, programmatic push ingestion, metadata transformation and UI-managed pipelines. · docs.datahub.com, 14 Oct 2026
Integrations
The project advertises more than 150 integrations, including Snowflake, BigQuery, dbt, Databricks, Looker, Tableau, Power BI, Airflow, Kafka, S3 and Iceberg. · docs.datahub.com, 14 Oct 2026
Investors
DataHub lists 8VC, LinkedIn, Bessemer Venture Partners, Next Play Ventures and other investors on its company page. · datahub.com, 14 Oct 2026
Licence
The open-source DataHub project is released under the Apache License 2.0. · github.com, 14 Oct 2026
Limit: data quality and dbt
Several G2 reviewers report missing or limited support for data-quality tests and dbt integrations. · g2.com, 14 Oct 2026
Limit: implementation effort
A G2 reviewer says teams must invest time and secure cooperation from data owners before the catalog delivers value. · g2.com, 14 Oct 2026
Limit: native integrations
A Gartner reviewer rates DataHub 4.0 and says it captures essential metadata but still has limited native integrations. · gartner.com, 14 Oct 2026
Limit: scale and interface
G2 feedback mentions slower or more cumbersome handling of very large datasets and occasional UI clunkiness. · g2.com, 14 Oct 2026

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