Amplitude to PostgreSQL: How to Move Your Data
Move Amplitude into PostgreSQL with Airbyte. Why only the dashboard streams belong here, and why Amplitude's own definitions are what you want.
Moving Amplitude into PostgreSQL suits an internal tool that needs product metrics beside your own data. A customer health view, an account dashboard or a service that checks usage before sending a renewal reminder all want those numbers where the application already reads.
This guide covers the managed path with Airbyte. Two things shape the build: only one half of what Amplitude offers belongs in this destination, and the half that does gives you Amplitude's own figures rather than your own.
Amplitude to PostgreSQL at a glance:
Why move data from Amplitude to PostgreSQL?
One situation genuinely suits this, and the other is worth naming.
The good case is serving an internal tool. Product metrics sitting beside account records let software answer questions like whether a customer's usage dropped before renewal, without anybody opening Amplitude or waiting on a warehouse query.
The poor case is raw event analysis, because event volume passes what this destination is comfortable holding and aggregating it here would be slow anyway. For that work, Amplitude to ClickHouse is the right shape.
What do you need before you start?
Four things, and the first is the decision this pipeline rests on:
A stream selection that excludes raw events. The dashboard streams are small and aggregated; the events export is where the volume lives and it does not belong here. The Amplitude source documentation lists what is available.
An API key, secret key and the correct data region. Keys are per project rather than per account, and the region setting defaults to the standard server, so an EU-hosted project needs that chosen explicitly.
A PostgreSQL database and an index plan. The pipeline creates tables and not indexes, and a serving copy without them is slower than the interface you were avoiding.
Agreement that these are Amplitude's numbers. The dashboard streams carry metrics Amplitude computed using its own definitions, which is usually what an internal tool wants and worth stating anyway.
If your database restricts inbound traffic by IP, add the Airbyte Cloud IP addresses to the allow list before you begin.
How do you build an Amplitude to PostgreSQL pipeline in Airbyte?
Step 1: Leave the events stream out
Decide before configuring anything that this pipeline carries dashboard metrics rather than raw events, because that single choice is what makes the pairing sensible. Events from an active product will fill this database and then keep going, and aggregating them here would be slow work in the wrong tool. The dashboard streams give you the numbers a tool displays, at a size nobody has to think about.
Step 2: Configure the Amplitude source
Click Sources in the left navigation, then New Source, and select Amplitude, following adding a source. Supply the API key, secret key, data region and start date. If the connection check fails, try disabling the option that groups active users by country, which the documentation names as a cause.
Step 3: Configure the PostgreSQL destination
Click Destinations, then New Destination, and select PostgreSQL, following adding a destination. Supply the host, port, database and credentials. Give this its own schema, and expect metadata columns to be added, so application code should select fields by name.
Step 4: Create the connection, then index for the tool
Click Connections, then New connection, select your streams and a sync mode. Daily suits product metrics. Then create indexes on whatever your tool filters by, usually a date and an account or user reference, before pointing an interface at the tables.
The dashboard streams throttle themselves against a cost budget, so there is nothing to tune once this is running.
Which half of Amplitude fits here?
The aggregated half. Amplitude exposes both raw event exports and dashboard metrics that it has already computed, and they behave nothing alike. Events are the volume, arriving in large exports capped by size; dashboard metrics are counts and averages that fit in a table nobody has to manage.
For an operational database that division is decisive. Guidance here is around ten gigabytes, and event volume from an active product passes it without any particular effort, after which you have a slow database and an unhappy application. The dashboard streams sit comfortably inside it and keep doing so.
The rate limits agree with that split, which is a pleasant coincidence. The dashboard API applies cost-based budgets the connector manages by throttling itself, so those streams need nothing from you, while the export API has a size ceiling that errors rather than slows. Taking only the aggregated streams therefore avoids the one part of this connector that requires supervision.
Whose definitions are these numbers?
Amplitude's, and for once that is the answer you want. Active user counts and session lengths are computed using Amplitude's rules about what counts as active and where a session begins, and taking them as given is the whole reason this arrangement is cheap.
That matters when your tool sits beside conversations with product teams. If an account manager sees a usage figure in your internal dashboard and a product manager sees one in Amplitude, those numbers agreeing is worth more than either being philosophically correct, and mirroring the source's definitions is how you get that.
Know the limit, though. If somebody needs active users defined the way the rest of your business defines them, that requires raw events and a different destination, and no amount of work here will produce it. Write down which definitions your tool is showing so the answer is available when the question arrives, as it eventually does.
Frequently asked questions
Should I sync raw events into PostgreSQL?
No. Event volume exceeds what this destination is comfortable holding, and aggregating it here would be slow. Take the dashboard streams instead.
The connection check fails.
Check the data region first, then try disabling the option that groups active users by country, which the documentation names as a cause of check failures.
Can I define active users my own way?
Not from these streams, which carry Amplitude's computed figures. Your own definition needs raw events and a destination suited to aggregating them.
Do I need to manage rate limits?
Not for the dashboard streams, which use cost-based budgets the connector throttles itself against. The export API is the part that needs supervision, and you are not using it.
Can I do this without writing code?
The pipeline, yes. The indexes and the views your tool reads are yours, and they are what makes this a serving layer rather than a copy.
Get your Amplitude data into PostgreSQL
Leave the events stream out, because that one decision is what keeps this pairing sensible and conveniently avoids the only part of the connector needing supervision. Set the data region explicitly. Then index for the queries your tool runs, and record that these are Amplitude's definitions, since mirroring them is a feature when your dashboard sits beside conversations with product teams.
Airbyte's connector catalog includes 600+ pre-built connectors, so product metrics can reach the tools your teams already use. For the same source into a warehouse, see Amplitude to Snowflake, and for the same source into another warehouse, Amplitude to BigQuery.
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