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

0.00 USD per 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 445.00 EUR per 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 50.00 USD per 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 3.00 USD per month, including 25 author licences, 125 collaboration licences and 20,000 metadata storage; optional secure hosting is 4.00 USD per 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.

	Apache Atlas	DataHub
Free plan	Yes	Yes
Free trial	No	Yes
Paid from	Free	Free
Open source	No	No
Platforms	api, Linux, self-hosted, Web	api, Linux, self-hosted, Web
Free plan	—	Yes
Metadata discovery	—	Yes
Business glossary	—	Yes
Lineage analysis	—	Yes
Deployment options	—	both
API available	—	Yes

Apache Atlas vs DataHub

Apache Atlas

DataHub