RSS to PostgreSQL: How to Move Your Data

Moving RSS into PostgreSQL turns a feed you would otherwise read into data you can query. Competitor announcements, regulatory notices, industry press and release notes all publish as feeds, and a feed reader is a poor place to ask when something was first mentioned or how often a topic comes up.

This guide covers the managed path with Airbyte. Two things shape the build: the RSS specification makes item identifiers optional, so there is no primary key at all, and incremental sync depends entirely on the feed publishing proper dates.

Rss to PostgreSQL at a glance:

Why move data from Rss to PostgreSQL?

Two situations account for most of these pipelines.

The first is monitoring that outlives a person's attention. Somebody is supposed to watch a regulator's announcements or a competitor's release notes, and in practice nobody does consistently. A table accumulating every item means the question can be asked later, including the questions nobody thought to ask at the time.

The second is joining published items to your own data, such as setting competitor announcements against your sales pipeline or support volumes. There is no serious volume argument for any other destination here, since feeds are tiny, so PostgreSQL is a sensible default rather than a compromise.

What do you need before you start?

Four things, and two of them are checks on the feed rather than on your infrastructure:

A feed URL. That is the entire source configuration, with no credentials to manage since feeds are public by nature. The RSS source documentation covers the setup and the fields you receive.

Confirmation that the feed publishes dates properly. Incremental sync uses the published date as its cursor, so every item needs a valid publication date. Plenty of feeds in the wild are sloppy about this, and it is a two-minute check that decides how the pipeline behaves.

A look at whether items carry a guid. The specification does not require one, so the connector has no primary key to offer. Whether the feed provides a guid anyway determines how easily you can deduplicate at your end.

A PostgreSQL database, and one source per feed. Each feed is its own source, so monitoring twenty publications means twenty sources. They are trivially small, but that is twenty things to configure and watch.

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 Rss to PostgreSQL pipeline in Airbyte?

Step 1: Inspect the feed before you trust it

Open the feed in a browser and look at the raw XML. Check that every item carries a publication date, since incremental sync depends on it, and check whether items carry a guid, since that is what you will deduplicate on later. Feeds are produced by all sorts of software of varying quality, and the difference between a well-formed feed and a careless one decides how much work the rest of this takes.

Step 2: Configure the RSS source

Click Sources in the left navigation, then New Source, and select RSS, following adding a source. Supply the feed URL, which is the only required field. One stream of items is available, carrying title, link, description, author, category and the rest as strings, with the date converted into a proper UTC datetime.

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. From version 3.0.0 the connector writes directly without intermediate raw tables and adds metadata columns, one of which becomes useful for the deduplication problem below.

Step 4: Create the connection and decide about duplicates

Click Connections, then New connection, select the stream and a sync mode. Because there is no primary key, deduplication is not something the pipeline can do for you, so decide now whether you handle it with a constraint, a view, or not at all. Hourly is plenty for most feeds, and many publish far less often than that.

Add an index on the published column, since almost every query against this table will filter or sort by it.

Why is there no primary key?

Because the RSS specification does not require one. An item may carry a guid intended to identify it uniquely, and it may not, so the connector cannot promise a primary key for feeds in general. What it offers instead is a cursor on the published date, which is enough to sync incrementally and not enough to tell two identical-looking items apart.

That has a practical consequence people meet quickly. Publishers edit items, republish them, or change a timestamp, and without a key the pipeline cannot recognise that it has seen something before. Your table therefore accumulates near-duplicates, and a count of articles published this month is wrong in a way that looks plausible.

The related trap is the cursor itself. Incremental sync works properly only when every item has a valid publication date, and a feed that omits dates or formats them oddly will behave unpredictably. Check that during your inspection, because the alternative is a pipeline that either misses items or re-reads the whole feed forever, neither of which announces itself.

How should PostgreSQL handle items it cannot identify?

By supplying the identity the feed did not. In most feeds the link is effectively unique per item even when guid is absent, which makes it a reasonable key to deduplicate on. A unique index on that column, or on a hash of link and published date together, turns an accumulating pile into something you can count.

Whether to enforce that with a constraint or express it in a view depends on what you want when a publisher edits an item. A constraint rejects the second version and keeps your first sighting, which suits monitoring where the question is when something first appeared. A view selecting the most recent row per link keeps the edits and shows current state, which suits a reading list. Both are defensible and they answer different questions.

The metadata columns the destination adds help here, since the extraction timestamp tells you when each row arrived and therefore which version is newer. Build your deduplicating view on that rather than on the published date, because the published date is under the publisher's control and the extraction timestamp is under yours. Then have everything downstream read the view rather than the raw table.

Frequently asked questions

Why does my table contain the same article twice?

There is no primary key, because the RSS specification makes item identifiers optional. Deduplicate yourself on the link, or on link and published date together.

Can I sync more than one feed from a single source?

No, a source takes one feed URL. Monitoring several publications means several sources, which is manageable since each is tiny but does multiply the things you maintain.

Incremental sync is behaving oddly.

Check that every item in the feed carries a valid publication date, since that is the cursor. Feeds that omit or mangle dates make incremental unreliable.

Are the fields typed?

Mostly not. Title, link, description, author and the rest arrive as strings, and only the date is converted into a proper UTC datetime for convenience downstream.

Can I do this without writing code?

The pipeline, yes, and it is the shortest setup in the catalogue. The deduplicating view or constraint is SQL, and without it your counts will be wrong.

Get your Rss data into PostgreSQL

Inspect the feed first, because whether items carry dates and identifiers decides everything that follows. Accept that there is no primary key and supply one yourself, usually the link, choosing deliberately between a constraint that keeps your first sighting and a view that shows the latest version. Build that view on the extraction timestamp rather than the published date, and index the published column since every query will use it.

Airbyte's connector catalog includes 600+ pre-built connectors, so public sources can be monitored alongside your own data. For a general API into the same destination, see Public API to PostgreSQL, and for another public dataset into the same destination, TMDB to PostgreSQL.

Start syncing now →