An Airbyte alternative for AI agents: managed data and SQL

Compare Combined with Airbyte Agents and Data Replication for business-data agents: SQL access, managed context, usage pricing, and a practical first workload.

Evaluate Combined as an Airbyte alternative when your existing AI agent needs governed SQL over synced business records. Combined brings ingestion, managed storage, schema discovery, and read-only MCP access into one workflow, with an initial 5 million MAR without a card and $5 per million MAR after the trial.

Compare the product your agent actually needs

Airbyte has two relevant offerings: Data Replication moves data into a destination you choose, while Airbyte Agents provides agent connectors and a managed Context Store. If you are building a business-data agent, compare the complete path from source authorization to a useful answer.

Three paths from business applications to agent context
OfferingData and access modelEvaluate it for
CombinedManaged synced datasets, scoped grants, and bounded read-only SQL through MCP.An existing agent that needs joins, exact filters, aggregates, and inspectable query results.
Airbyte AgentsA managed Context Store plus connector operations through MCP, API, SDK, and CLI.Agents that combine indexed business-data search with live connector actions.
Airbyte Data ReplicationReplication into a selected destination, with managed and self-managed options.A data stack where you want to choose the destination and assemble the agent query layer.

Airbyte’s Context Store supports filtering, sorting, and aggregation over a curated selection of source entities and fields. Some connectors also support semantic search. Its agents can use direct API requests for current records, unsupported entities, and writes. Those capabilities matter when comparing it with a read-only data layer.

Combined’s appeal is the SQL workflow: discover the granted logical datasets, inspect their schemas, check freshness, and query them with the agent you already use. Your team can focus on business questions without separately operating the ingestion destination and its agent-facing query service.

Start with the business question, then compare the answer

A useful evaluation question crosses the boundary between two applications. For example, a CRM can tell you which companies have open opportunities, while billing records can show their paid invoices. Giving an agent access to both is only useful if it can connect the records correctly.

Using the granted CRM and billing datasets, find companies with open
opportunities and summarize their paid invoices from the last 90 days.

First discover the schemas and check source freshness. Establish a
shared company identifier before joining; don't join on company name
alone. Aggregate each side before joining so multiple deals don't
duplicate invoice totals. Keep currencies separate.

Return at most 20 companies, with open opportunity value, paid invoice
total, the time window, source timestamps, and the query receipt.
If a matching key or required field is missing, explain what is needed.

In Combined, the agent uses catalogue discovery and describe_dataset to learn the available fields, then query_sql for the bounded analysis. The important output is a result you can inspect: a clear join, consistent time bounds, separate currencies, and an explanation of the data’s age. This is a worked evaluation prompt; adapt it to the datasets you have connected.

Start smaller if one source is enough. The HubSpot tutorial walks through pipeline analysis; the Claude Code guide covers the MCP connection. Use the same question and permitted fields when evaluating another platform.

Compare changed records with agent operations

Combined’s public rate is $5 per million monthly active records after the trial, with no public base charge or minimum. MAR measures changed records at the committed data boundary. The initial cardless allowance is 5 million MAR. Query budgets are separate: the default monthly input budget is 100 GiB per account, with a 256 MiB estimated-input ceiling per query.

Airbyte Agents meters agent operations, or AOs, which represent processing work rather than a fixed number of requests. Bring your own agent through MCP, API, SDK, or CLI and Airbyte counts tool-call work, not that external agent’s reasoning. Airbyte-hosted Chat includes reasoning; local open-source SDK connector calls do not consume AOs.

Airbyte Agents plans, checked September 10, 2026
PlanMonthly priceIncluded AOs per month
Free$01,000; no overage
Individual$295,000; overage available
Team$29910,000; overage available

Airbyte’s billing documentation lists Free and Individual as self-serve, with Team and Custom sales-assisted. Free refreshes the Context Store hourly for two weeks, then daily; Individual and Team refresh hourly.

One million MAR and one thousand AOs describe different work. Estimate your source changes, query sizes, and agent activity before comparing bills. Combined is straightforward to size around changing business records; Airbyte Agents requires sizing the agent’s operations. A trial allowance and a recurring free plan also serve different stages of the evaluation.

Try Combined with one source and your existing agent

You can evaluate Combined alongside your current stack. Pick one question worth answering, confirm the source’s Ready status and required object coverage, connect it, and sync the selected datasets. Grant the agent access to that scope and use the account-specific connection instructions in the Access workspace.

Choose Combined when you want managed business data with explicit SQL over granted relations. If the same agent also updates CRM records or sends messages, pair that read path with the appropriate action integration. Keep each source’s freshness and the permissions required for the job visible in the workflow.

See how Combined brings business context to your agent, then start with the cardless allowance below. Get one useful answer, inspect the result, and expand to the next source when the next question needs it.

Sources and further reading

Explore the documentation behind this guide. Product details checked on September 10, 2026.