"Data pipeline" is a phrase that makes a company of eight feel it is missing something. In most cases it is missing a Tuesday morning: one person, one hour, four tabs open — Google Ads, Meta, Analytics, the CRM — copying last week's numbers into the sheet the Monday meeting looks at. That hour is the pipeline. It is manual, it is late, and it is not wrong.
The tools in this comparison replace that hour. Whether replacing it is worth money depends on three questions, and only three:
- How many sources? Two platforms and Analytics is a different problem from nine.
- How often? Weekly numbers for a meeting, or daily numbers for a dashboard somebody actually opens?
- Who reads the result? A person in a spreadsheet, a Looker Studio report, or a database that other tools query?
Feature counts do not decide: Windsor.ai lists more than three hundred connectors, Fivetran more than 700, and a company of eight uses four or five.
Disclosure first: Grünberg.Digital uses Windsor.ai itself, on an existing account, for the ad platforms. For everything it owns — leads, newsletter results, the search console export, the editorial plan — it writes its own exports. One column below is a tool we pay for, another a method we practise; we say where our own export loses.
1. Windsor.ai: the connector priced for marketing
Windsor.ai prices by data sources, meaning platforms such as Google Ads or Meta, and by the number of accounts within them — not by rows. Its published plans, billed annually, are Basic $19, Standard $99, Plus $249 and Professional $499 per month; billed monthly they are $23, $118, $299 and $598. Basic covers 3 data sources and 75 accounts with a daily sync and five destination tasks, Standard 7 sources with hourly syncs and unlimited destination tasks, Plus 10 sources, Professional 14 sources with syncs down to 15 minutes. Every paid plan has unlimited users and unlimited syncs into BI tools such as Looker Studio; Enterprise is priced on request. There is a 30-day trial, after which a free plan remains with one user, one data source and one account, and the FAQ states there are no setup or onboarding fees (Windsor.ai pricing page, checked 22 September 2026).
That suits marketing data, which is wide but not deep. For the reference company, Google Ads, Meta and Analytics into a Looker Studio report, Basic is the natural fit: $228 a year, $684 over three years. The setup is an afternoon, and the Tuesday hour disappears.
The number to watch is the fourth source. Add the CRM, Search Console or LinkedIn and the company moves from Basic to Standard, from $19 to $99 a month — a fivefold step, $1,188 a year, $3,564 over three years. That is the same ceiling we pointed out at Supermetrics, whose Starter plan costs $44 a month for three data sources and whose Growth plan $177 for six, billed annually ($55 and $222 billed monthly; Supermetrics pricing page, checked 22 September 2026). Windsor.ai is cheaper at both steps and includes more users, but it does not avoid the step. Standard then holds seven sources, more than a company of eight usually needs.
Where Windsor.ai stops being the answer: when the data has to land somewhere that is not a report or a sheet. The moment the CRM wants to read the ad cost per lead back, or the editorial plan wants to write search console rows into its own table, the destination is a database you control. Windsor.ai can write into BigQuery, but then you have a warehouse.
2. Fivetran: the pipeline priced for data teams
Fivetran is the reference product for "data pipeline" in the strict sense: extract, load into a warehouse, transform there. It charges by monthly active rows (MAR) — rows inserted or updated in a calendar month; since 1 January 2026, deletes count too. The Free plan includes 500,000 MAR a month for connections and 5,000 model runs for transformations. On the Standard plan, every connection that generates between 1 and 1 million MAR carries a $5 monthly base charge, and the rate per row then falls with volume. Fivetran does not publish that rate as a number; it offers an estimator and worked examples — a Facebook Ads connection with 34,479 MAR at $22.06 a month, Google Analytics 4 with 21,993 MAR at $15.88. Annual contracts save up to 22 percent, and there is a 14-day trial (Fivetran pricing page and 2026 pricing update notes, checked 22 September 2026).
Two things follow. Fivetran's bill grows with the data, not the number of sources — right for a company that already runs BigQuery or Snowflake and employs somebody who writes SQL. And, less expected: a small marketing stack is not a lot of rows. Fivetran's own examples for Facebook Ads and Analytics add up to about 56,000 MAR — roughly a ninth of the free allowance. For the reference company, the connector itself may well cost nothing.
That does not make it cheap; it makes price the wrong question. Fivetran delivers into a warehouse the company does not have, for an engineer the company does not employ, and it leaves the transformation — turning raw ad rows into the five numbers the Monday meeting wants — to that engineer. The warehouse has its own bill, not covered here; the engineer's days are the real cost.
The exception: a company whose product is data — a shop with order histories, a SaaS with usage events — outgrows marketing connectors early, and for it Fivetran beats building a dozen extractors.
3. Your own export: the script with a schedule
The third column is a scheduled script: it calls each platform's API nightly, writes the rows into a table, and a report reads the table. In our experience it costs a developer one to two days per source to build, runs on hosting the company already pays, and needs about an hour a quarter per source to keep working, because platform APIs change, tokens expire and fields get renamed.
We do this for everything we own, not for the ad platforms. That split is where most small companies with a technical person end up:
- Own the export where you own the source. Your CRM, your sender, your website: the API is yours, it does not change without you, and a connector would be paying somebody to read your own database — assuming a connector for it exists at all. For a self-built CRM like ours, none does.
- Buy the connector where you do not. Google, Meta, LinkedIn: their APIs change on their schedule, and the connector vendor's business is noticing first.
4. Where our own export loses
It loses on price, first, wherever a connector exists. Building the three ad and analytics exports ourselves would cost three to six developer days — 2,400 to 4,800 euros at an assumed rate of 800 euros a day — before a single maintenance hour. Windsor.ai Basic costs $684 for three years. There is no reading of that comparison in which the script wins.
It loses on failure, second: the script that ran nightly for nine months and stopped in month ten because a token expired is the classic case. It fails silently, and the Monday meeting looks at stale numbers with fresh dates. A connector has a status page. A script has whoever wrote it, on holiday exactly when it breaks.
What it wins is narrow and specific: the data lands in your own database, other tools can query it, and there is no subscription attached to your own data.
5. The three-year bill for a company of eight
Four sources — Google Ads, Meta, Google Analytics 4 and the CRM's leads — into one report for a weekly meeting, three years, published US-dollar list prices on annual billing as cited above, taxes left out. Own work is priced at an assumed 800 euros per developer day and 50 euros per hour for the person doing the manual export; replace both with your own figures.
- The manual Tuesday hour — 52 hours a year, 156 hours over three years; at the assumed rate 7,800 euros, with no invoice and no setup.
- Windsor.ai Standard, all four sources — $99 a month, $1,188 a year, $3,564 over three years; setup an afternoon. On monthly billing $4,248.
- Windsor.ai Basic plus our own CRM export (our split) — Basic for three sources, $684 over three years, plus one to two days to build the CRM export and four hours a year to maintain it, 2,000 to 2,800 euros on top.
- Fivetran Free plus a warehouse — $0 for the connector as long as the stack stays under 500,000 MAR a month; the warehouse is billed separately and the modelling is developer work. On Standard, the base charge alone is at least $5 per connection, $240 a year or $720 over three years for four, before the rows.
- Everything self-built — four to eight days to build, 3,200 to 6,400 euros, plus 16 hours a year of maintenance, 1,600 euros a year: 8,000 to 11,200 euros over three years.
- Who notices when it breaks — Windsor.ai and Fivetran: the vendor, on a status page. Own export: you, when the numbers look odd.
Read across. The manual hour costs more than any connector and never shows up on an invoice; Windsor.ai Standard is the cheapest complete answer without a developer. Our split is not cheaper than Windsor.ai Standard when the CRM export has to be built from nothing; it wins only when that export exists already or when the data has to live in your own database anyway, which for us it does. Building everything yourself is the most expensive column by a distance, and it is the one we do not recommend.
6. Verdict: the Tuesday hour decides
- If the Tuesday hour is the whole problem — three or four sources, a weekly meeting, a sheet or a Looker Studio report — Windsor.ai replaces it for $19 or $99 a month, which is less than the hour costs at almost any wage, and the comparison ends there.
- If the numbers have to flow back into your own tools — cost per lead into the CRM, search rows into the plan — build the export for the sources you own and buy a connector for the ones you do not. That split is cheaper than building everything and, with the owned exports in place, it is where we landed.
- If you have a warehouse and an analyst, you were never the audience for this piece; Fivetran's consumption pricing is designed for you, and at small volumes it starts at nothing.
And if the Tuesday hour is happening and nobody minds — leave it. A pipeline that replaces an hour nobody resents is a subscription nobody needed. That is the conclusion of our twelve-tools comparison, and it holds for pipelines as for the CRM three-year bill: price the tier you will actually be on, not the one on the front page.
Would you like to know which of the three shapes your numbers are? Book a free initial consultation — bring the list of sources and the Monday sheet, and the answer is a short conversation.
7. FAQ: marketing data pipelines for small companies
Does a small company need a data pipeline at all?
Only if the manual export — typically one person, one hour a week, several platforms into a sheet — is late, wrong or resented. If it is none of those, the hour is the pipeline. If it is any of those, a marketing connector on an entry tier replaces it for less than the hour costs.
What does Windsor.ai cost?
Billed annually, Basic costs $19 a month for three data sources, Standard $99 for seven, Plus $249 for ten and Professional $499 for fourteen; billed monthly $23, $118, $299 and $598. All paid plans include unlimited users; there is a 30-day trial and a free plan with one data source afterwards, and no setup fees. Prices from Windsor.ai's pricing page, checked 22 September 2026.
What does Fivetran cost for a small marketing stack?
Fivetran charges by monthly active rows. The Free plan includes 500,000 MAR a month, which a small ad and analytics stack often stays under. On Standard, each active connection carries a $5 monthly base charge plus a volume rate shown only via an estimator. The warehouse is billed separately. Checked 22 September 2026.
Windsor.ai or Fivetran for marketing data?
Windsor.ai is priced by sources and built to feed reports and sheets; Fivetran is priced by rows and built to load a warehouse for analysts. A company of eight without a warehouse is almost always in Windsor.ai's territory.
When is a self-written export better than a connector?
For sources you own — your CRM, your newsletter sender, your website — where the API does not change without you and the data needs to land in your own database so other tools can use it. For third-party platforms, a connector is cheaper and its value is that someone else absorbs the API changes; a self-written script fails silently when a token expires.
What does maintaining a self-built export cost?
Roughly an hour per source per quarter, plus the risk of silent failure: the script stops, the dates look fresh, the numbers are stale. Building in a check that flags a source with no new rows is the single most valuable hour spent on a self-built pipeline.
