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Dawiso empowers over 24,000 daily data users worldwide

Why choose Dawiso
over DataHub?

DataHub OSS Core is open and capable, but production self-hosting is a real platform-engineering project: Kafka, Elasticsearch, a metadata store, the GMS backend and a separate frontend, all stood up, tuned and maintained by your team. Dawiso is managed in every deployment option - SaaS, your Azure, or on-prem - with the same features on every plan and no self-hosted infrastructure to operate.

Compare Dawiso vs. DataHub on your own data in 30 minutes.

Trusted by leading enterprises

Dawiso is trusted by data-driven teams across industries

Dawiso vs DataHub

Built on real customer feedback and publicly available sources. For deeper insights, book a 30-minute live demo on your own data.

Features Dawiso DataHub
Deployment and operations Managed in every option (SaaS, your Azure, or on-prem) with 100% feature parity and same-tier support on every plan - no self-hosted infrastructure to run OSS Core is a self-hosted multi-service stack (Kafka, Elasticsearch, metadata store, GMS, frontend) needing a dedicated platform team; SLA-backed 99.5% availability and a dedicated customer success team are positioned as DataHub Cloud
Time to production 2-4 weeks, managed 6-12 weeks OSS self-host, longer with governance lifecycle positioned as Cloud
Open-source story One product, one feature set, no upgrade tax OSS Core is genuinely open; certification workflows, governance automations, shift-left governance positioned as DataHub Cloud
Governance workflows Approval flows, lifecycle states, Excel import/export included Governance-lifecycle tooling (certification workflows, no-code automations) is positioned as DataHub Cloud
AI agents and MCP Managed production MCP read+write (Databricks MCP Marketplace), Technical Writer Agent in every plan, Agentic Data Governance Steward Q3 2026 DataHub's MCP server (acryldata/mcp-server-datahub) is self-hosted - you run and maintain it against your own instance; Cloud adds managed MCP and advanced agentic features
Total cost trajectory Predictable per-seat, every feature in every plan OSS free but engineering-heavy; Cloud pricing is opaque (Enterprise on request)

Where Dawiso runs in production

A named enterprise case study and rotating G2 community reviews. Both running today.

Kooperativa Customer case study

“Significantly accelerated work, fewer errors and delays”

Dawiso automatically loads millions of objects from databases and data models, presenting and making them accessible to users from various departments in a meaningful way. As a result, the work of analysts and developers has significantly accelerated, and the number of errors and delays in working with data has decreased.

Kooperativa

Insurance, Vienna Insurance Group - 2.4M clients

Read full case study
G2 1 / 3

The Ultimate Data Maze Transparency

“We have a clear overview of data flows. Before Dawiso, it was a bit complicated to see where the data comes from and to have all the sources documented in one place. Dawiso made this easy with its comprehensive data lineage. We also build on a unique capability in data modeling, which allows us to set up an optimal data design process. Support is always there for us when needed.”

Jan K.

Business Solution Data Architect

More on G2

Efficient Implementation: Domain Expertise and Partnership

“Utilizing strong expertise in initial discussions and building robust partnerships during implementation led to exceptional results, enabling the project to go live in a very short timeframe.”

Michal P.

Data engineer

More on G2

Dawiso Product Review

“The interface is clean and intuitive, which makes it incredibly easy to navigate, even for someone who isn't particularly tech-savvy. I found it easy to locate the tools and features I needed, saving time and minimising any learning curve. The user-friendly dashboard provides a clear overview of all key metrics, and it feels like a natural extension of my workflow.”

Amy C.

Customer

More on G2
G2 Reviews Gartner Peer Insights capterra badge

Top-rated by data teams

Verified reviews on G2, Gartner Peer Insights, and Capterra.

Comparison of G2 ratings

Verified user reviews on G2, reflecting real-world experiences.

CRITERIA
Dawiso
DataHub
Ease of Use
9.7
8.6
Ease of Setup
9.4
7.8
Quality of Support
9.4
8.4
Data Lineage
9.3
8.7
UI/UX
9.6
8.5

Price comparison

What you actually pay per user, per month. Based on public pricing and reported deal sizes.

Total cost of ownership score, 0-10. Lower is better.
Dawiso
2.1/10
Collibra
9.8/10
Ab Initio
6.8/10
Atlan
5.6/10
Select Star
5.0/10
DataHub
4.1/10
OpenMetadata
4.1/10
Alation
3.2/10
DataGalaxy
2.7/10
Secoda
2.6/10

TCO scores anchor on public AWS Marketplace starting subscription pricing, normalized 0-10 where lower is better. Full 3-year program cost varies by services SOWs, paid modules (DQ, lineage, AI agents), and steward FTE. Methodology updated 2026-05.

Feature by feature

What you actually get, side by side.

Five capabilities most buyers care about. One row each. No fine print, no SKU shopping.

GLOSSARY

Business glossary

Governance ships with the product, not behind a paywall
Dawiso Logo dawiso Winner
Wiki-style, AI-assisted, Excel-ready
  • Long structured definitions, formal approval flows
  • Excel import/export for bulk term migration
  • Role-based editing per term and per domain
DataHub Logo DataHub Limited
OSS glossary without bulk workflows
  • OSS version missing Excel import/export for term curation
  • Approval workflows and lifecycle states sit in DataHub Cloud
  • Cross-domain term modelling requires custom YAML and ingestion code
AI

AI Context Layer

Production agents and MCP on day one, not after a contract
Dawiso Logo dawiso Winner
Native MCP + agentic stewards
  • MCP server, REST, embeddings in every plan
  • Agentic data steward + technical writer included
  • No separate vector store, no Cloud upgrade required
DataHub Logo DataHub Limited
OSS MCP shipping; managed agentic features Cloud-gated
  • DataHub OSS ships acryldata/mcp-server-datahub on GitHub (self-hosted, fully featured)
  • DataHub Cloud adds managed MCP and advanced agentic features
  • No pre-built Technical Writer Agent or Agentic Data Governance Steward in OSS or Cloud
LINEAGE

Live data lineage, editable in-product

Live and editable, not batch-ingested
Dawiso Logo dawiso Winner
Auto + manual edits, column-level, real-time
  • Live lineage from warehouse and transformation tools
  • Edit edges in-product where the parser misses
  • Impact analysis on every schema change
DataHub Logo DataHub Limited
Ingestion-driven lineage with manual gaps
  • Lineage depends on recipe ingestion runs, not real-time observation
  • Manual lineage edits require custom emitter code, not in-product fixes
  • Column-level coverage uneven across BI and transformation tools
DEPLOYMENT

Managed catalog vs a self-hosted platform you run

Managed and complete, not a stack you operate
Dawiso Logo dawiso Winner
Delivered managed in every deployment option
  • Managed in every option: SaaS, your own Azure, or on-prem - no self-hosted infra to operate
  • One product, one data model: business and technical metadata linked by design, with the same features on SaaS, Azure and on-prem
  • Same-tier support on every plan - reliability and customer success aren't paywalled to an enterprise tier
  • In-product customization of schemas, workflows and roles - no services engagement, and fast time-to-value with 40+ connectors (2-4 weeks)
DataHub Logo DataHub Limited
OSS Core is open, but production self-hosting is a platform-engineering commitment
  • Production self-hosting stands up Kafka, Elasticsearch, a metadata store, the GMS backend and a separate frontend - reviewers note it needs significant engineering investment for setup, tuning and maintenance
  • Realistically viable with a dedicated platform team running Kafka/Elasticsearch/Kubernetes (production guidance: 16GB+ RAM, 4+ cores on dedicated infra)
  • Governance-lifecycle tooling - certification workflows, governance automations, shift-left governance, no-code automations - is positioned under DataHub Cloud
  • SLA-backed 99.5% availability and a dedicated customer success team are positioned as DataHub Cloud; OSS Core users rely on community support and carry their own uptime
PACKAGING

Procurement model

Open about packaging, not open-source theatre
Dawiso Logo dawiso Winner
One product, every feature, every plan
  • No OSS-to-Cloud upgrade tax for governance features
  • AI and MCP included, not a Cloud-only add-on
  • Predictable per-seat, no per-table metering
DataHub Logo DataHub Limited
OSS framed as open, Cloud holds the governance
  • OSS version missing Excel import/export, lifecycle, approval workflows
  • Self-hosting OSS is engineering-heavy (Kafka, Elasticsearch, GMS, frontend)
  • DataHub Cloud bills per-table at scale, with advanced AI behind the same gate

Dawiso connects to your entire data landscape

Modern data stacks are complex. Bring your entire tech stack into one connected view. Scan, ingest, and catalog every piece of metadata.

Teradata
Databricks
Kafka
Keboola
Amazon Redshift
Microsoft SQL Server
Snowflake
Power BI
Qlik
Data Lake
Oracle
PostgreSQL
MySQL
WhereScape
SAP HANA
REST API
Excel
PowerDesigner
Tableau
Jira
dbt
GitLab
Teradata
Databricks
Kafka
Keboola
Amazon Redshift
Microsoft SQL Server
Snowflake
Power BI
Qlik
Data Lake
Oracle
PostgreSQL
MySQL
WhereScape
SAP HANA
REST API
Excel
PowerDesigner
Tableau
Jira
dbt
GitLab
GitLab
dbt
Jira
Tableau
PowerDesigner
Excel
REST API
SAP HANA
WhereScape
MySQL
PostgreSQL
Oracle
Data Lake
Qlik
Power BI
Snowflake
Microsoft SQL Server
Amazon Redshift
Keboola
Kafka
Databricks
Teradata
GitLab
dbt
Jira
Tableau
PowerDesigner
Excel
REST API
SAP HANA
WhereScape
MySQL
PostgreSQL
Oracle
Data Lake
Qlik
Power BI
Snowflake
Microsoft SQL Server
Amazon Redshift
Keboola
Kafka
Databricks
Teradata
ABC logoKPMG LogoPWC LogoRandom ForestNei ConsultingPROFINIT LogoDolphin consulting

Dawiso partners with leading data consultancies to support smooth implementation across industries

Why teams switch to Dawiso

Built for data teams who want results, not complexity.

No DevOps team required

DataHub OSS Core needs Kafka, Elasticsearch, a metadata store, GMS and a separate frontend stood up, tuned, and kept alive. Dawiso is managed in every deployment option (SaaS, your Azure, on-prem) with 100% feature parity - your team configures the catalog, not the platform underneath it.

Same features on every plan, no Cloud-gated lifecycle

Approval flows, lifecycle states, governance automations and SLA-backed reliability are positioned as DataHub Cloud. Dawiso ships the full feature set and same-tier support on every plan.

Managed MCP and agents on day one

DataHub's MCP server is self-hosted - you run and maintain acryldata/mcp-server-datahub against your own instance. Dawiso's MCP Server is managed and production-hosted with read+write (published in the Databricks MCP Marketplace), and the Technical Writer Agent ships in every plan.

Frequently asked questions

Everything you need to know about the comparison. Can't find the answer you're looking for? Contact us and we will answer you in a short time
Is DataHub OSS Core free, and does that make it cheaper than Dawiso?

DataHub OSS Core is open source, but "free" shifts cost rather than removing it. Production self-hosting means a dedicated team standing up and maintaining Kafka, Elasticsearch, a metadata store, the GMS backend and a frontend, so the real total cost includes that infrastructure and operations work. DataHub Cloud pricing is opaque - the Enterprise tier is available on request with no published dollar amounts - so buyers can't budget either path upfront easily. Dawiso is managed in every deployment option with the same features and support on every plan, so there's no self-hosted ops burden and no "the operational features live in the paid tier" split.

How long does migration from DataHub take?

Two to four weeks is the typical Dawiso rollout end-to-end. Migration from DataHub adds a metadata export through the OSS APIs and a mapping pass into Dawiso, which most teams complete inside one additional sprint. Dawiso open APIs make the export and re-ingest path straightforward.

Can we run DataHub and Dawiso in parallel during evaluation?

Yes. Point both at the same warehouse, give a small business team a 30-day shadow trial on Dawiso, and compare governance adoption side by side. Most teams notice the operations gap (managed catalog vs. self-hosted Kafka/Elasticsearch/GMS) within the first sprint.

When does DataHub still make sense?

If you have a platform team that wants to own and operate the stack, accepts the Cloud-positioned governance-lifecycle and SLA tooling, and has dedicated engineers to run Kafka, Elasticsearch, and GMS long-term, DataHub OSS Core can fit. If you want the catalog managed for you - same product, same features and same support on every plan - that is the Dawiso case.

Ready to see why teams pick Dawiso over DataHub?

Book a 30-minute live demo on your own data, or take the comparison home as a PDF.

Download full comparison