A Fivetran alternative for AI agents: ingestion, storage, and MCP
Evaluate Combined for the whole path from business apps to agent answers: managed ingestion, storage, scoped MCP access, and $5 per million MAR after the trial.
Combined is a Fivetran alternative to evaluate when your goal is to give an AI agent queryable business data. It brings source connection, managed storage, and scoped, read-only MCP access into one workflow. Start with an initial 5 million MAR without a card; usage after the trial is $5 per million MAR.
Compare the whole path to an agent answer
A connector is the start of the job. Your agent also needs to find the right datasets, understand their fields, access them with the right permissions, and return a useful answer. When you evaluate an ingestion service for an AI application, include that complete workflow in the decision.
Combined is built around that path. Connect business sources, sync selected records into managed storage, and expose granted data through SQL, MCP, or the documented SDK interfaces. Your agent discovers the data and queries it; your team can inspect source freshness and query receipts.
| Decision | Combined’s approach | What to establish for an alternative |
|---|---|---|
| Getting the data | Authorize a Ready source and select its datasets and fields. | Required connector, supported objects, credentials, and update behavior. |
| Keeping it queryable | Managed storage and logical datasets inside the Combined account. | The chosen destination and who operates the query layer. |
| Giving an agent access | Scoped grants and bounded, read-only SQL through MCP. | How the agent authenticates, discovers schemas, and queries permitted records. |
| Understanding the answer | Freshness information and query receipts. | How to establish the source, coverage, and age of the returned data. |
Fivetran has multiple destination options, including managed data lakes. Compare the offering you would actually use. An existing warehouse and mature data team create a different decision from a small team trying to ship its first business-data agent.
A clear starting allowance and a simple usage rate
Combined starts with an initial 5 million monthly active records, or MAR, without a card. After the trial, the public usage rate is $5 per million MAR. The pricing page explains the allowance, billable activity, and query limits so you can size a first workload before connecting it.
| Billable MAR | Calculation | Charge at the public rate |
|---|---|---|
| 1 million | 1 × $5 | $5 |
| 2 million | 2 × $5 | $10 |
| 10 million | 10 × $5 | $50 |
These are calculations at the published rate, not measured customer bills. MAR describes billable record activity; a source’s stored row count alone does not tell you its ongoing usage. Include the initial load and expected changes when sizing the connection, using the MAR definition.
Fivetran also offers cardless signup and a recurring free plan that currently includes up to 500,000 monthly active records. Combined’s 5 million MAR starting allowance is a trial allowance, not a recurring free tier. Compare the current terms and the complete workload, including its destination and agent access, instead of comparing the two allowance numbers as equivalent plans.
Choose Combined when the agent is the destination
Combined is a strong fit for a developer, small AI team, or forward deployed engineer who wants to turn business applications into context for an existing agent. You can start with one source and one useful answer, then add data as the application grows.
- Business analysis: filter, group, and aggregate granted structured records with SQL.
- Coding-agent context: connect a compatible MCP client such as Claude Code.
- Client work: organize the source connection and agent access within the relevant account.
- Operational clarity: inspect sync state, freshness, and query receipts in the workflow.
Keep the evaluation tied to your actual sources. Confirm each connector’s Ready status, object coverage, and authorization requirements. If the job needs writes back into a business application, use an appropriate write integration alongside the read-only data path. For semantic similarity search, evaluate that retrieval layer separately.
The managed-ingestion checklist helps compare the source, storage, freshness, and access requirements. It is a practical way to choose a platform around the work your agent needs to do.
Get to your first business answer
Start with a question that currently causes a spreadsheet export. Open pipeline by stage is a useful first example: connect HubSpot, select the deals data, sync it, and let the agent discover the fields before running a read-only aggregate.
The HubSpot guide includes the connection steps and a copyable analysis prompt. The Claude Code tutorial shows how to add Combined’s MCP endpoint and verify a query. Use the account-specific setup instructions in your workspace for your own connection.
Bring the question and the agent. Combined handles the managed business-data workflow behind the answer. Start with the cardless allowance, inspect the result, and connect the next source when the next question needs it.
Sources and further reading
Explore the documentation behind this guide. Product details checked on September 9, 2026.