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Dawiso empowers over 24,000 daily data users worldwide

Why choose Dawiso
over DataGalaxy?

DataGalaxy is a capable European catalog whose flexibility reviewers describe as a "double-edged sword" - it works well only if you are certain how the system should model your processes, and reviewers note it "requires a good design phase at the start," with a service-partner ecosystem positioned to run the full project cycle. Dawiso is configured in-product - schemas, workflows and roles set up by your own team - with a read+write MCP Server and pre-built agents, live in 2-4 weeks without a mandatory design-phase or consulting engagement.

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

Trusted by leading enterprises

Dawiso is trusted by data-driven teams across industries

Dawiso vs DataGalaxy

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

Features Dawiso DataGalaxy
Time to production 2-4 weeks, no services SOW required 6-12 weeks typical; design phase recommended up front
Time-to-value & configuration model Schemas, workflows and roles configured in-product by your team; 2-4 week time-to-value, no required services engagement Reviewers note the high flexibility "requires a good design phase at the start" and a service-partner ecosystem is positioned to run the full project cycle (use cases, implementation, training)
AI agents and MCP Production MCP read+write (Databricks MCP Marketplace), Technical Writer Agent in every plan, Agentic Data Governance Steward Q3 2026 DataGalaxy MCP Server exposes catalog context to external AI assistants (read-only context); in-product AI (Metabot, Auto Description) runs in suggestion/assist mode
Customization model Schemas, workflows, roles configurable in-product Highly configurable, but reviewers warn flexibility "only works if you are 100% certain of how you want the system to reflect your data processes"
Connector breadth 40+ native plus open APIs across modern SaaS stack Solid on common SQL warehouses, lighter on modern transformation tools

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

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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
DataGalaxy
Ease of Use
9.7
8.6
Ease of Setup
9.4
8.4
Quality of Support
9.4
8.9
Data Lineage
9.3
8.7
Active Metadata Management
9.5
8.3

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

Same modelling depth with agents on top
Dawiso Logo dawiso Winner
Wiki-style, AI-assisted, governed
  • Long structured definitions with formal approval flows
  • Role-based editing rights per term and per domain
  • Inline AI suggestions for definitions, owners, related terms
DataGalaxy Logo DataGalaxy Limited
Functional glossary, light AI assist
  • Glossary modelling is competent on the basics
  • No inline AI suggestions, definitions are typed manually term by term
  • Cross-linking to dashboards and tables takes more manual work
AI

AI Context Layer

Agent-native out of the box
Dawiso Logo dawiso Winner
Native MCP + agentic stewards
  • MCP server, REST, embeddings in every plan
  • Agentic data steward and technical writer included
  • Claude, ChatGPT, Copilot ground on your real metadata
DataGalaxy Logo DataGalaxy Limited
MCP shipping; no pre-built agentic stewards
  • DataGalaxy MCP Server (datagalaxy.com/en/product/mcp-server) exposes catalog context to AI agents
  • No pre-built Technical Writer Agent or Agentic Data Governance Steward ships out of the box
  • In-house agents can ground on metadata via MCP; pre-built agent layer is the Dawiso add
LINEAGE

Live data lineage, editable in-product

Live and editable across the modern stack
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
DataGalaxy Logo DataGalaxy Limited
Solid auto, light manual editing
  • Automatic lineage works on common SQL warehouses
  • In-product manual editing is constrained when parsing gaps appear
  • Column-level coverage depends on connector tier
CUSTOMIZATION

Configurable in-product vs front-loaded design phase

Configure in-product in weeks, not through a partner
Dawiso Logo dawiso Winner
Set up by your own team, in-product, in weeks
  • Schemas, workflows and roles are customizable in-product by the customer, not via a vendor engagement
  • 2-4 week time-to-value - no required design-phase or consulting engagement to get going
  • Same-tier support on every plan, so configuration help isn't gated behind an enterprise tier
  • Single product, one data model - business and technical metadata linked by design, nothing to stitch together
DataGalaxy Logo DataGalaxy Limited
"Double-edged sword" flexibility, partner-led delivery
  • Reviewers warn the flexibility only works "if you are 100% certain of how you want the system to reflect your data processes"
  • Reviewers say it "requires a good design phase at the start to make a successful implementation"
  • DataGalaxy positions a service-partner ecosystem to run "the entire project cycle, from structuring use cases, to implementation and team training"
  • Some reviewers note limited local administration of certain config items (e.g. tags) and UX customization that "lacks a bit of maturity" - though others praise its configurability
PACKAGING

Procurement model

Ship-ready out of the box, not out of an SOW
Dawiso Logo dawiso Winner
One product, every feature, every plan
  • No SKU shopping, no tier-gated capabilities
  • AI agents and MCP included, not premium add-ons
  • Same support SLA on every contract size
DataGalaxy Logo DataGalaxy Limited
Custom quote, mid-market positioning
  • No public per-seat list price, every deal is custom-quoted
  • Advanced lineage and premium connectors priced as separate add-ons
  • Public proof at large-enterprise scale is thin outside the EU mid-market

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.

Configure in-product in weeks, not through a partner

Schemas, workflows and roles are configured directly in Dawiso, with a 2-4 week time-to-value. No required design-phase, no service-partner engagement to stand up the catalog.

Read+write MCP and named agents, not read-only context

DataGalaxy MCP Server exposes catalog context to external assistants; in-product AI (Metabot, Auto Description) runs in suggestion/assist mode. Dawiso ships a read+write MCP Server (Databricks MCP Marketplace), the Technical Writer Agent in every plan, and the Agentic Data Governance Steward shipping Q3 2026 - agents that act inside the catalog.

Same-tier support on every plan

No design-phase paywall, no partner gate. Same response SLA on every contract size, whether you are fifty seats or five thousand.

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
Can we set up and adapt the catalog ourselves, or do we need a consulting engagement?

With Dawiso, your team configures schemas, workflows and roles directly in-product, with a 2-4 week time-to-value and no required services engagement. DataGalaxy can be self-configured too, but reviewers note its flexibility "requires a good design phase at the start," and DataGalaxy positions a service-partner ecosystem to run the full project cycle - so many deployments lean on a consulting or partner engagement to stand up and adapt the catalog.

How long does migration from DataGalaxy take?

Two to four weeks is the typical Dawiso rollout end-to-end. Migration from DataGalaxy adds a metadata export and a glossary mapping pass for terms, ownership, and lineage edges. Most teams complete that inside one additional sprint, which is faster than a fresh DataGalaxy deployment usually lands.

Can we run DataGalaxy and Dawiso in parallel during evaluation?

Yes. Point both at the same warehouse, route a small business team to Dawiso for a 30-day shadow trial, and compare adoption side by side. We support this evaluation pattern explicitly and ship the connectors, glossary, and agentic stewards on day one so the comparison is honest from week one.

When does DataGalaxy still make sense?

DataGalaxy has built a competent glossary product and a steady EU mid-market motion. If your committee is comfortable running a design-phase up front, working with a delivery partner, and the in-product AI (Metabot, Auto Description) in assist mode meets your AI needs, DataGalaxy fits the shape of that program. If you want to configure the catalog yourself in weeks and ship read+write MCP-grounded agents that act inside the catalog, that is the Dawiso case.

Ready to see why teams pick Dawiso over DataGalaxy?

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

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