Dataddo
No-code data pipelines that also write straight into dashboards and business apps
Dataddo is a fully managed, no-code data integration platform that moves data between more than 300 sources and destinations, including warehouses, dashboarding tools, and business applications. Unlike warehouse-only ELT services, it can deliver data directly into Google Sheets, Looker Studio, Power BI, and operational tools, which makes it usable by marketing and operations teams with no data engineering function.
Overview
Most data integration platforms assume a warehouse exists and a data team maintains it. Dataddo assumes neither. Its connectors move data from marketing, sales, finance, and product sources to whatever destination the customer actually uses, which for a large share of small businesses is a spreadsheet or a Looker Studio dashboard rather than Snowflake. That single design choice defines its market.
The platform is fully managed in the strongest sense: connectors are maintained by the vendor, API changes are absorbed without customer involvement, and there is no infrastructure to run or code to write. Flows are configured through a web interface, with basic transformation, field selection, filtering, and blending, available before delivery so the destination receives usable data rather than raw dumps.
Its position is between spreadsheet connectors and full ELT platforms. It is more capable and more reliable than a marketing data add-on, and less powerful and less extensible than Fivetran or Airbyte. Pricing per flow rather than per row makes costs predictable, which is often more valuable to a small business than raw capability, and the Czech company has built a reputation for responsive support and quick connector additions.
Best for
Small and mid-sized businesses, marketing teams, and agencies that need reliable automated reporting from many sources without a data engineer, particularly where the destination is a dashboard or spreadsheet rather than a warehouse.
Not the right fit for
- Data engineering teams needing deep transformation, custom connectors, or self-hosting.
- Very high volume replication where per-flow pricing and managed extraction are less efficient than dedicated ELT.
- Reverse ETL use cases requiring sophisticated identity resolution and audience logic.
- Organizations wanting open source or on-premise deployment.
- Teams whose main need is behavioral event collection rather than periodic data movement.
How it works
- 1
You authenticate a source, choose which metrics, dimensions, or objects to extract, and configure the schedule. Extraction settings are exposed in a form rather than requiring API knowledge.
- 2
Optional processing happens in the flow: selecting fields, filtering rows, renaming columns, and blending multiple sources into one output so a dashboard reads a single table rather than joining five.
- 3
The flow writes to a destination: a cloud warehouse, a dashboarding tool such as Looker Studio, Power BI, or Tableau, a spreadsheet, or a business application. Warehouse and non-warehouse destinations are treated equally, which is the platform's distinguishing choice.
- 4
Dataddo monitors flows, retries failures, and notifies on problems, with the vendor maintaining connectors as source APIs change so the customer never edits an integration.
Feature breakdown
20 features in 4 modulesSources and destinations
Breadth in both directions, including non-warehouse targets.- Three hundred plus connectors
- Marketing, advertising, social, CRM, finance, ecommerce, and analytics sources with vendor-maintained authentication and extraction.
- Dashboard destinations
- Direct delivery into Looker Studio, Power BI, Tableau, and Google Sheets, which most ELT platforms do not support at all.
- Warehouse destinations
- Snowflake, BigQuery, Redshift, Postgres, and other warehouses for teams that do have one.
- Application destinations
- Write-back to business tools, enabling simple operational flows rather than only reporting.
- Connector requests
- New sources added by the vendor on request, typically within weeks, which is the practical alternative to a development kit.
Flow configuration
Transformation enough to make the output usable.- Field and metric selection
- Choose exactly which fields to extract, keeping outputs narrow and readable rather than dumping whole objects.
- Filtering and row rules
- Restrict what is delivered at extraction time, reducing volume and destination clutter.
- Data blending
- Combine several sources into one output table so a dashboard reads a single dataset rather than joining across connectors.
- Scheduling control
- Per-flow frequency from hourly to monthly, matched to how often the underlying data actually changes.
- Historical backfill
- Load past data on setup so reporting has history from the first day rather than starting empty.
Management and reliability
The managed part of fully managed.- Vendor-maintained connectors
- API changes handled by Dataddo without customer intervention, the core promise of a managed service.
- Flow monitoring and alerts
- Failure notifications and run history so a broken report is noticed before someone reads a stale dashboard.
- Automatic retries
- Transient failures and rate limits handled without operator involvement.
- Team access
- Multiple users with permissions, and account structures suitable for agencies managing client data.
- Responsive support
- Direct support access including on lower tiers, which is a consistent theme in customer feedback.
Commercial model
Predictability as a feature.- Per-flow pricing
- Cost driven by number of flows rather than rows processed, which makes budgeting straightforward.
- Free plan
- A permanent free tier covering a small number of flows, enough to automate one recurring report.
- Unlimited users
- Seats are not the meter, so a whole team or agency can access the platform without per-user cost.
- Unlimited sources per plan
- Connector variety is not gated, so a marketing team can pull from many platforms without upgrade friction.
- Agency arrangements
- Structures for managing many client accounts, a substantial part of the customer base.
Use cases
4 documentedMarketing manager assembling a monthly report
Data from six ad platforms, GA4, and the CRM is copied into a spreadsheet by hand every month.
Flows deliver all sources into one blended Google Sheet or Looker Studio dataset on a schedule, and the manual assembly disappears.
Agency reporting across client accounts
Each client needs a dashboard, and per-row pricing from other vendors makes small accounts unprofitable.
Per-flow pricing with unlimited users keeps cost predictable across a portfolio of small clients.
Finance analyst combining billing and ad spend
Profitability analysis needs Stripe revenue alongside advertising cost, currently reconciled manually.
Both sources land in a warehouse or spreadsheet on the same schedule, blended into one table ready for analysis.
Small company with no data team but a new warehouse
A BigQuery project exists but nobody can build pipelines into it.
No-code flows populate the warehouse from business systems, giving a data foundation without hiring for it.
Pricing
from Free for a small number of flows; paid plans from roughly $99 per monthSubscription priced by number of active flows and sync frequency, with unlimited users and sources on paid plans. A free tier covers a small number of flows, and higher tiers add frequency, volume, and support.
| Plan | Price | Includes |
|---|---|---|
| Free | $0 per month |
|
| Data to Dashboards | From about $99 per month |
|
| Data Anywhere and Headless | From about $199 per month |
|
Billing notes
- Flows, not rows, are the meter, which makes cost predictable and favors many small datasets over a few enormous ones.
- Sync frequency affects the plan required, so hourly reporting costs more than daily even at the same flow count.
- Unlimited users means agencies and larger teams are not penalized for access, unusual in this category.
- Connector requests are handled by the vendor rather than requiring development, which is effectively an included service.
- Prices as published August 2026; plan structures have been revised periodically.
Value assessment: Dataddo is priced for businesses whose alternative is manual copying rather than a data engineering team, and against that alternative it is straightforwardly cheap. The per-flow model protects small accounts from the row-based escalation that makes ELT platforms awkward for agencies. Against Fivetran or Airbyte it offers less depth and no extensibility, but for the reporting automation that most small businesses actually need, the extra capability would go unused.
Strengths & limitations
Strengths
- Delivers directly into dashboards and spreadsheets, not only warehouses, which matches how small businesses work.
- Genuinely no-code and fully managed, requiring no engineering involvement at all.
- Predictable per-flow pricing with unlimited users and sources.
- Data blending before delivery removes joins from the dashboard layer.
- Vendor adds requested connectors, which substitutes effectively for a development kit.
- Consistently well-regarded support, including on lower tiers.
Limitations
- Transformation is basic; anything complex belongs in a warehouse with dbt.
- No self-hosting, open source, or custom connector development.
- Less suited to very high volume replication than dedicated ELT platforms.
- Not a behavioral event collection tool, so it does not replace a CDP for product analytics.
- Reverse ETL capability is simple compared with dedicated activation platforms.
- Smaller brand presence than the major ELT vendors, which occasionally matters in procurement.
Head-to-head comparisons
3 alternativesDataddo vs Supermetrics
from €49 per month (Starter), or €39 per month billed yearlyThe closest competitor for marketing reporting. Supermetrics has deeper coverage and refinement in advertising and marketing sources specifically, with a strong spreadsheet heritage. Dataddo is broader beyond marketing, covering finance, CRM, and product sources, with per-flow pricing rather than per-source licensing. Marketing-only teams often prefer Supermetrics; teams reporting across the whole business prefer Dataddo.
Full Dataddo vs Supermetrics comparisonDataddo vs Airbyte
from Free self-hosted; Cloud usage-based with a trial credit, commonly from tens of dollars per month at small volumesDifferent buyers entirely. Airbyte is engineer-oriented, open source, extensible, and warehouse-focused, with more connectors and more variance. Dataddo is fully managed no-code with dashboard destinations and predictable pricing. A company with a data team should use Airbyte; a company whose analyst works in Looker Studio should use Dataddo.
Full Dataddo vs Airbyte comparisonDataddo vs Databox
from $0 (Free), then $64 per month billed annually (Analyst)Complementary or overlapping depending on setup. Databox is a dashboarding and KPI platform with its own connectors; Dataddo is a pipeline that can feed dashboards including Databox-style destinations. Teams that want dashboards and pipelines from one vendor may choose Databox alone; teams that already have a preferred BI tool use Dataddo to feed it.
Full Dataddo vs Databox comparisonImplementation & onboarding
- Setup time
- Minutes per flow once source credentials exist. A full reporting stack covering a dozen sources is typically configured in a day.
- Learning curve
- Low. The interface is aimed at marketers and analysts, and the concepts, source, flow, destination, schedule, are the whole model.
- Onboarding
- Self-serve with documentation and responsive support, plus assistance configuring complex blends on higher tiers.
- Migration notes
- Moving from manual reporting is additive rather than disruptive. Moving from another pipeline tool requires rebuilding flows and checking that field naming matches what existing dashboards expect, since a renamed column silently breaks a report.
Platform, API & security
- Platforms
- Web applicationCloud serviceAPI access on higher tiers
- API
- REST API for flow management and data retrieval on appropriate plans, plus embedded and headless use for partners.
- Compliance
- GDPRCCPASOC 2ISO 27001
- Data residency
- EU-based processing available, appropriate to its European base.
- SSO
- Available on higher tiers.
- Security notes
- Field selection at extraction limits what sensitive data moves at all, which is a simple and effective control for teams without a formal governance function.
Support & resources
- Channels
- Email supportIn-app chatDocumentation and onboarding assistance
- Documentation
- Clear connector-level documentation aimed at non-technical users, with configuration guidance per source.
- Community
- Modest but positive presence, with the company's reputation resting more on support responsiveness than on community scale.
Company
- Founded
- 2018
- Headquarters
- Prague, Czech Republic
- Ownership
- Private, independent
- Employees
- ~80 (est. 2026)
- Funding
- Raised modest venture funding.
Timeline
- 2018Founded in Prague as a no-code data integration platform for business users.
- 2020Expands dashboard destinations, differentiating from warehouse-only ELT vendors.
- 2022Adds warehouse and application destinations, covering both ends of the market.
- 2024Grows the connector catalogue past 300 with vendor-managed request handling.
- 2026Established as a leading no-code option for businesses automating reporting without a data team.
Integrations
- Google Analytics 4
- Google Ads
- Meta Ads
- LinkedIn Ads
- HubSpot
- Salesforce
- Stripe
- Shopify
- Looker Studio
- Power BI
- Google Sheets
- Snowflake
Frequently asked questions
10 questionsWhat is Dataddo?
Dataddo is a fully managed, no-code data integration platform that moves data between more than 300 sources and destinations. Unlike warehouse-only ELT tools, it can deliver directly into dashboards and spreadsheets such as Looker Studio, Power BI, and Google Sheets, as well as into cloud warehouses.
How much does Dataddo cost?
There is a free plan covering a small number of flows. Paid plans start around $99 per month and are priced by number of active flows and sync frequency, with unlimited users and sources included. Per-flow rather than per-row pricing makes costs predictable as data volumes grow.
Do I need a data warehouse to use Dataddo?
No, and that is the main thing distinguishing it from most competitors. Data can go straight into a dashboard tool or spreadsheet, which is where a large share of small business reporting actually lives. Warehouse destinations are supported for teams that do have one.
Dataddo vs Supermetrics: which is better?
Supermetrics is deeper and more refined for marketing and advertising sources specifically, with a strong spreadsheet heritage. Dataddo covers a broader range of business systems and prices per flow rather than per source. Marketing-only reporting favors Supermetrics; cross-functional reporting favors Dataddo.
Can Dataddo transform data?
It supports field selection, filtering, renaming, and blending multiple sources into one output, which is enough to make dashboards read cleanly. Anything more substantial belongs in a warehouse with dbt or SQL; Dataddo deliberately does not attempt to be a transformation platform.
What happens when a source changes its API?
Dataddo maintains the connector and absorbs the change, which is the core promise of a fully managed service. Customers do not edit integrations, and there is no code to update, which is precisely why non-technical teams can rely on it.
Can Dataddo connect to a source it does not support?
There is no self-service connector kit, but the vendor accepts connector requests and typically adds them within weeks. For most small businesses this works better than a development kit, since the alternative would be building and then maintaining the connector themselves.
Is Dataddo suitable for agencies?
Yes, and agencies are a significant part of its customer base. Unlimited users, per-flow pricing, and support for many client accounts keep the per-client cost workable even on small retainers, which row-based pricing models tend not to do.
Does Dataddo do reverse ETL?
It can write to some business applications, which covers simple operational flows, but it is not a dedicated activation platform. Teams needing identity resolution, audience logic, and sophisticated sync behavior into CRM and marketing tools should look at Hightouch or Census.
How often can data sync?
Frequency depends on the plan, ranging from hourly on higher tiers to daily or less often on cheaper ones. Since sync frequency is one of the pricing levers, match it to how often the underlying data genuinely changes rather than defaulting to the highest available.
Editorial verdict
Dataddo understands something most data integration vendors ignore: a great many businesses do not have a warehouse and never will, but they still spend hours every month copying numbers between platforms. By treating a Looker Studio dataset or a Google Sheet as a first-class destination, and by pricing per flow with unlimited users, it makes reporting automation affordable for exactly the buyers other tools price out. It is not deep, not extensible, and not the right choice for a data engineering team. For a marketing team, an agency, or a small company with more platforms than analysts, it removes a recurring chore reliably and cheaply, which is a more useful thing to buy than capability nobody will use.
Written by the SaaSTracker editorial team. Awards, when shown, are judged against the published criteria in our methodology.