An integration count is a marketing number. Every product tool publishes one, none of them define it the same way, and the gap between the largest and smallest catalogue tells you almost nothing about which will fit your stack. This is how to compare them in a way that survives contact with your actual work.
Which product platforms have the most integrations available?
Every major vendor claims somewhere between roughly one hundred and several thousand integrations, and the numbers are not comparable. The counts mix one-way webhooks, Zapier passthroughs, read-only imports and genuine two-way syncs into a single figure. A catalogue of 300 shallow entries and one of 100 deep ones look like a 3:1 advantage on a comparison page and produce the opposite experience on a Tuesday afternoon.
The useful question is not how many, but what the connector does and where it writes.
The four properties that separate a connector from a logo
Most catalogue entries fail at least one of these. Checking them takes about ten minutes per connector and replaces the entire count comparison.
| Property | The question to ask | Why it decides things |
|---|---|---|
| Scheduled | Does it sync on its own, or only when something triggers it? | A connector you have to poke is a script with a logo. |
| Identity-mapped | Does it match records by a stable id, or by name and email? | Name-matching quietly creates duplicates that corrupt every count downstream. |
| Full lifecycle | Does it handle updates and deletes, or only creates? | Create-only syncs drift within weeks and nobody notices until a number looks wrong. |
| Two-way | Can you write back, or only read? | This is what decides whether your team can close the other tab. |
Vendors describe the fourth loosely more than any other. "Syncs with Jira" frequently means it reads Jira. Change something on your side and nothing arrives. Test it by changing a record in each direction before you commit.
What a shallow entry looks like in practice
Three patterns account for most of the padding in a large catalogue, and each one is easy to spot once you know the shape.
The Zapier passthrough. The logo is on the page; clicking it explains that you connect via a third-party automation platform, on your own account, with your own quota. This is a real capability and a legitimate thing to offer - it is not a first-party integration, and counting it as one is what lets a catalogue reach four figures.
The one-time importer. It moves your history across on day one and does nothing afterwards. Genuinely valuable during a migration, worthless as an ongoing connection, and indistinguishable from a sync on a feature grid. The question that separates them: after the import, does tomorrow's change arrive?
The notification hook. Something happens, a message is posted. Useful, but it moves no records and creates nothing you can query later. A catalogue heavy with these is describing an alerting surface, not an integration layer.
None of the three is bad. All three are worth having. The problem is only that a single number treats one of them as equal to a scheduled, identity-mapped, two-way sync, and buyers reasonably assume the number means the latter.
The question underneath the question
People asking which tool has the most integrations are rarely collecting connectors. They are trying to stop doing something specific: exporting from three systems into a spreadsheet to answer a question that spans all three.
That is why the count is the wrong metric. Connectors that feed separate destinations do not reduce that work - they industrialise it. You end up with feedback in one tool, usage in another, delivery in a third and revenue in a fourth, all beautifully synced, and the question "which of the features we shipped last quarter kept a paying account" still requires four exports and an afternoon.
Connectors that feed one shared record change the shape of the work. The same afternoon becomes a query, because the customer, their revenue, their requests, the work you did and the usage that followed are all attached to the same object.
So the honest comparison is:
- Catalogue length - how many things can be connected at all.
- Sync depth - how many of the four properties above each connector actually has.
- Convergence - how many separate places the connected data lands in.
The third is the one nobody publishes and the one that determines whether connecting anything helped.
How we think about it
AIOProductOS ships 100+ live connectors across 18 categories - payments, code and infrastructure, support, analytics, communication and the rest - plus inbound webhooks for anything not in the catalogue. That number is subject to exactly the criticism above, so the part worth stating is the design decision behind it: every connector writes into the same spine, so a Stripe subscription, a GitHub pull request, an Intercom conversation and a product event all attach to one customer record rather than to four parallel copies.
That is the whole reason the catalogue exists. We would rather have a connector that lands in the shared record than three that land in separate ones.
When a bigger catalogue genuinely is the right call
This is a real trade-off and pretending otherwise would be dishonest.
If your problem is breadth of automation rather than joined analysis - you need this niche CRM to talk to that niche billing system, and the two have nothing to do with your product decisions - then the widest possible catalogue is exactly right, and a general automation platform will beat any product tool. Zapier and its equivalents exist for this and are good at it.
Likewise, if the specific system you depend on is unusual, a vendor with 2,000 shallow connectors is more likely to have yours than one with a curated few hundred. Coverage beats depth when the alternative is no connection at all. Check whether your critical systems are present before evaluating anything else in this article - a deep catalogue that omits your billing provider is not a candidate.
And if you have a data team who already own a warehouse, the honest answer may be that you do not want product-tool integrations at all. Pipe everything into the warehouse, model it there, and treat product tools as sources rather than destinations.
A ten-minute test that beats any comparison page
Do this once, with a trial account, before you read another feature grid.
- Pick your four. Billing, issue tracker, support inbox, analytics - whichever four you would genuinely connect in the first month. Not the ones you might connect eventually.
- Connect one and wait. Do not trigger anything. Come back an hour later and check whether new records arrived on their own. If they did not, it is not scheduled, whatever the page says.
- Rename something. Change a company or account name on the source side. If the connector matches on names, you will see a duplicate rather than an update - the single most common cause of counts that quietly stop adding up.
- Delete something. Deletes are the most commonly unimplemented half of a sync, and the one that leaves you with records that exist nowhere else.
- Write back. Change a status in the product and check the source system. This is the direction that decides whether anyone on your team can stop keeping both tabs open.
- Ask a spanning question. Pick something that needs two of the four connected systems at once - "which accounts that requested this also churned" is a good one - and see whether you can answer it without exporting anything.
Step six is the whole evaluation. The first five tell you whether the connectors work; the sixth tells you whether connecting them accomplished the thing you wanted.
What to do with all this
Take the three or four systems you would actually need connected - usually billing, your issue tracker, your support inbox and your analytics - and check only those, against the four properties. Ignore the rest of the catalogue entirely; you will never use most of it. Then ask where the connected data lands, and whether that lets you answer the question that made you start looking.
If the answer is still "export three systems into a spreadsheet", the count was never the problem.
See the full connector catalogue with what each one syncs and in which direction, or read how the shared spine joins them. If you want to check the two-way behaviour without an account, the live demo runs on real connected data.