TL;DR Short answer: the best RSS ETL tools depend on whether you want an archive or an alert. To keep every item from many feeds in a warehouse, use a connector such as Airbyte or a small Python pipeline; to react to new items, use Zapier, Make, n8n or Pipedream. Whatever you choose, plan for two quirks of RSS itself: items often have no reliable identifier, and feeds only show recent items, so history must be built by syncing regularly. Eight RSS ETL tools compared:
Airbyte Zapier Make n8n Pipedream Google Sheets IMPORTFEED dlt Custom code with feedparser The RSS constraint: the RSS specification makes item identifiers optional and most feeds show only recent items, so deduplication and history are your job, whichever tool you pick. RSS ETL tools collect items from RSS and Atom feeds, such as news, blogs, release notes, job postings and status pages, and land them in a cloud data warehouse , spreadsheet or application. Teams use them for media and competitor monitoring, content curation and alerting, often alongside their own business data.
An RSS feed is a machine-readable file, written in XML, that a website publishes to list its latest content. Each entry in the feed, called an item, carries a title, a link, a short description and usually a publication date. Instead of visiting a site to check for updates, a feed reader or an RSS ETL tool requests the feed on a schedule and picks up anything new.
RSS stands for Really Simple Syndication. Blogs, news sites, podcasts, job boards, GitHub releases, status pages and many content management systems publish feeds by default, which makes RSS one of the most widely available ways to collect structured updates from the web without scraping.
A feed reader is built for people reading items one at a time. RSS ETL tools are built for data: they poll feeds on a schedule, keep items after they drop off the feed, and put them where you can search, count, join or act on them. That is the difference between reading the news and analysing which competitors published what, and when.
Feed readers such as Feedly or Inoreader are the right choice when the goal is reading. Once you need to count items, compare publishers over time, join items with your own data or trigger actions automatically, the job has moved from reading to data integration, and RSS ETL tools fit better.
Tool Best for Approach Deployment Pricing model Airbyte Archiving feeds in a warehouse RSS source, incremental by published date Airbyte Cloud, Airbyte Flex, self-hosted Airbyte Core Free self-hosted Core; Cloud volume-based; Pro and Flex capacity-based Zapier Simple alerts and hand-offs RSS by Zapier trigger Cloud Task-based plans, free tier Make No-code routing RSS modules in scenarios Cloud Operations-based plans, free tier n8n Self-hosted automation RSS read and trigger nodes Cloud or self-hosted Free self-hosted; paid cloud plans Pipedream Developer workflows New-item trigger plus code steps Cloud Credit-based plans, free tier Google Sheets IMPORTFEED Quick spreadsheet views Built-in formula Google Sheets Included with Google Workspace dlt Python teams loading a warehouse Python resource with schema handling Wherever you run Python Free, open source Custom code Exact control feedparser library Wherever you run it Free, engineering time
Eight RSS ETL tools, from warehouse connectors to automation platforms and code:
1. Airbyte Airbyte is the open-source data connectivity platform for AI and analytics, and among RSS ETL tools it is the one built for keeping an archive. Its RSS source reads a single items stream with title, link, description, author, category and guid, converts the publication date into a UTC timestamp, and syncs incrementally using that date as the cursor. For more ELT options, see our guide to ELT tools .
Two limits come from RSS itself rather than the connector. Each source takes one feed URL, so twenty publications means twenty sources, and because the specification makes guid optional the connector has no primary key, so edited or republished items can arrive again and should be deduplicated on the link in your warehouse. Airbyte runs in Airbyte Cloud, in your own environment with Airbyte Flex, or self-hosted with Airbyte Core.
Key features Incremental syncs: the publication date acts as the cursor, so each run reads only items published since the last sync and appends them to the destination.Normalised dates: publication dates in the many formats feeds use are converted to UTC ISO timestamps, so items from different publishers sort and join correctly.Consistent schema: every item lands with the same fields, including title, link, description, author, category, comments, enclosure and guid, whichever publisher it came from.Any destination: items can go to Snowflake, BigQuery, Postgres, S3, Elasticsearch or any other Airbyte destination, next to data from 700+ other sources.Best for: teams that want a long-term, queryable archive of many feeds next to their own business data, without maintaining polling code.
Pricing: self-hosted Airbyte Core is free; Airbyte Cloud plans are billed on volume, and Pro and Airbyte Flex on capacity.
Pros Cons Incremental sync on publication date One source per feed URL Builds a permanent archive in your warehouse No primary key, so deduplicate downstream No credentials needed for public feeds Incremental sync needs valid dates on every item
2. Zapier Zapier's built-in RSS by Zapier app triggers a workflow when a new item appears in one feed or across several, then sends it to Slack, email, a CRM, a spreadsheet or hundreds of other apps. It suits alerting and simple hand-offs rather than building an analysable history. How often feeds are checked depends on your plan.
Key features Triggers: New Item in Feed watches one feed, and New Items in Multiple Feeds watches several feeds at once and fires for each new item.Create Item in Feed: Zapier can also publish items to an RSS feed it hosts for you, which is a quick way to turn form submissions, emails or app events into a feed others can subscribe to.Filters and formatting: Filter and Formatter steps can keep only items matching keywords and clean up titles, dates or HTML before passing them on.Polling interval: Zapier checks feeds every 15 minutes on the free plan and as often as every one to two minutes on higher paid plans.Best for: non-technical teams that want new items posted to Slack, email or a CRM within minutes, with no infrastructure.
Pricing: a free plan with a monthly task allowance; paid plans are billed on tasks, and each item that passes through a Zap uses tasks.
Pros Cons Fast to set up with no code Task-based pricing grows with volume Monitors several feeds in one trigger Not built for historical archives Thousands of destination apps Polling interval depends on plan
3. Make Make's RSS modules watch feeds for new items or retrieve current items inside visual scenarios, which can filter, transform and route each item to databases, sheets, chat tools or AI steps. It suits teams that want more control over the flow than a simple trigger gives.
Key features RSS modules: Watch RSS feed items triggers on new items, while Retrieve RSS feed items fetches the current items on demand inside a scenario.Routers and filters: one scenario can send items to different destinations depending on keywords, author or category.Iterators and aggregators: Make can loop over items, batch them into a daily digest, or combine several feeds into one output.AI steps: items can be summarised, classified or translated with AI modules before they reach their destination.Best for: teams that want visual, multi-step feed workflows with more branching than a single trigger allows.
Pricing: a free tier with a monthly usage allowance; paid plans are billed on usage, with shorter scheduling intervals on higher tiers.
Pros Cons Visual scenarios with filters and routers Operations-based pricing adds up Can enrich items before routing Not a warehouse loading tool Free tier to start Scenario complexity grows quickly
4. n8n n8n provides an RSS Read node and an RSS Feed Trigger, so workflows can poll feeds on a schedule or react to new items, then filter, summarise and send them on. It can be self-hosted, which suits teams that want automation without a per-task bill.
Key features RSS Read and RSS Feed Trigger: the Read node fetches a feed when a workflow runs, and the Trigger node polls a feed and starts a workflow for each new item.Code nodes: JavaScript or Python nodes can parse custom fields, deduplicate items or reshape them for a database.AI and LLM nodes: items can be summarised, tagged or scored with AI models before being stored or sent.Self-hosting: n8n runs on your own server or in Docker, so polling volume does not drive a per-task bill.Best for: technical teams that want self-hosted automation for feeds and are comfortable running their own instance.
Pricing: the self-hosted Community edition is free under n8n's Sustainable Use License, which is fair-code rather than OSI open source; n8n Cloud is a paid managed service.
Pros Cons Self-hosting option You run and maintain it if self-hosted RSS read and trigger nodes Deduplication is up to your workflow Code nodes for custom logic Less suited to large backfills
5. Pipedream Pipedream offers a new-item-in-feed trigger and lets you add Python or Node.js steps, so developers can parse, enrich and store items without managing servers. It sits between no-code automation and writing your own service.
Key features RSS triggers: New Item in Feed and New Item From Multiple RSS Feeds sources emit only items they have not seen before, which handles basic deduplication for you.Code steps: Python or Node.js steps can parse, enrich and transform items, with access to npm and PyPI packages.Built-in storage: data stores can keep state between runs, such as the last item processed or a list of seen links.Prebuilt actions: items can be sent to databases, Slack, email, Google Sheets and many other apps without writing integration code.Best for: developers who want to write a little code without running servers or schedulers.
Pricing: a free tier for testing and light use; paid plans are credit-based, with credits consumed by workflow runs.
Pros Cons Code steps in Python or Node.js Credit-based pricing at volume Managed infrastructure Still your logic to maintain Many prebuilt app actions Not built for warehouse-scale archives
6. Google Sheets IMPORTFEED Google Sheets has a built-in IMPORTFEED function that pulls items from an RSS or Atom feed into a sheet with one formula, refreshed periodically by Google. It is the quickest way to watch a few feeds, though it shows only what is currently in the feed and does not keep history. For more spreadsheet options, see our guide to Google Sheets ETL tools .
Key features Syntax: IMPORTFEED(url, [query], [headers], [num_items]) imports a feed into the sheet, for example =IMPORTFEED("https://example.com/feed", "items title", TRUE, 10).Query options: query selects what to return, such as "items" for everything, "items title", "items url", "items created" or "items summary", or "feed title" for feed-level details.Item limit: num_items sets how many items to import, and the function returns 20 by default.Refresh: Google refreshes import functions periodically, roughly every hour, while the spreadsheet is in use.Best for: people who want to watch a handful of feeds in a sheet with zero setup.
Pricing: free with any Google account. To keep history, pair it with a short Apps Script that copies new rows to another sheet on a timer.
Pros Cons No setup beyond a formula Shows only current feed items Free with Google Workspace Refresh timing controlled by Google Easy to share Not suited to many feeds or large volumes
7. dlt dlt is an open-source Python library for loading data. Paired with a feed parser, a short dlt resource loads items into DuckDB, BigQuery, Snowflake or Postgres with schema handling and incremental loading on the publication date, which suits Python teams that want a warehouse archive in code. For more code-first options, see our guide to Python ETL tools .
Key features Incremental loading: dlt.sources.incremental on the publication date loads only new items on each run.Merge on link: setting the item link as the primary key with a merge write disposition updates edited items instead of duplicating them.Schema evolution: new fields, such as a publisher adding media tags, are added to the destination table automatically.Many destinations: the same pipeline can load DuckDB locally for testing and BigQuery, Snowflake or Postgres in production.Best for: Python teams that want a warehouse archive defined in code, versioned and scheduled with the rest of their pipelines.
Pricing: free and open source under the Apache 2.0 licence; you pay only for where it runs and where the data lands.
Pros Cons Schema handling and incremental loading You run and schedule it Loads to many destinations Requires Python skills Free and open source No hosted UI
8. Custom code with feedparser When no RSS ETL tools fit a narrow need, parse feeds yourself. feedparser is the standard Python library for RSS and Atom, handling malformed feeds and date formats, and you control polling, storage and deduplication. For broader API pipelines, see our guide to REST API ETL tools .
Key features Format coverage: it parses RSS 0.9x, RSS 1.0, RSS 2.0 and Atom feeds into the same Python structure.Normalised dates: it parses the many date formats feeds use into published_parsed and updated_parsed values, ready to store as timestamps.Malformed feeds: it still parses broken feeds where possible and sets a bozo flag, so you can log or skip bad sources rather than crash.Conditional requests: passing the etag and modified values from the previous fetch lets servers return 304 Not Modified, which saves bandwidth and is polite to publishers.Best for: engineers with a narrow, well-defined need who want complete control over polling, storage and deduplication.
Pricing: free and open source; the cost is the engineering time to schedule, store and monitor it.
Pros Cons Full control over parsing and storage You own scheduling and retries Handles RSS and Atom variants Deduplication and history are on you No licence cost Ongoing maintenance
Whichever RSS ETL tools you choose, most problems come from the feeds themselves. Check these first:
Publication dates: incremental syncs depend on every item having a valid date. Open the raw feed and check before relying on it.Identifiers: guid is optional in RSS, so plan to deduplicate on the item link, and expect edited items to reappear.History: most feeds show only the latest items, so start syncing early and run often enough that nothing scrolls off between runs.Feed count: many tools treat each feed separately, so estimate how many sources or workflows you will maintain.Content: feeds often include summaries rather than full articles. Store the link if you need the full text.Terms of use: check how publishers allow their content to be stored and displayed.RSS and Atom feeds expose items with fields such as:
Title and link: the headline and the URL of the full item. Description: a summary or the full content, depending on the publisher. Author and category: who wrote it and how the publisher tagged it. Publication date: when the item was published, the basis for incremental syncs. Enclosure and guid: attached media such as podcast audio, and an optional identifier. What is the difference between RSS and Atom? Atom is a newer feed format, standardised by the IETF in 2005, designed to fix ambiguities in RSS. The practical differences for ETL are:
Identifiers and dates: Atom requires a unique id and an updated timestamp for every entry, while RSS 2.0 makes guid and pubDate optional, which is why RSS items are harder to deduplicate.Content type: Atom labels content as text, HTML or XHTML, while RSS leaves it to the reader to guess what the description contains.Date format: Atom dates follow one standard format, while RSS dates follow an older format that publishers often get wrong.Most tools in this guide read both formats, so in practice you can treat them the same, while expecting cleaner data from Atom feeds.
Most sites do not link their feed prominently, but it is usually easy to find:
Common URLs: try common paths such as /feed, /rss, /rss.xml, /atom.xml or /index.xml on the site's domain.Page source: view the page source and search for application/rss+xml or application/atom+xml, which marks the feed link browsers and readers use to auto-discover feeds.Platform patterns: WordPress sites publish a feed at /feed, and category or tag feeds at /category/name/feed; YouTube channels, Reddit communities and GitHub repositories also publish feeds for uploads, posts and releases.No feed: if a site has no feed at all, RSS ETL tools cannot help, and you would need an API or a scraper instead; see our guide to web scraping tools .If you decide to test Airbyte, setting up an RSS pipeline takes three steps.
Step 1: Set up RSS as a source Open the feed in a browser and check that every item has a publication date. In Airbyte, open Sources, choose New source, select RSS and enter the feed URL, which is the only field. Repeat for each feed you want to follow.
Step 2: Set up a destination Pick where your feed items should land, such as BigQuery, Snowflake, Postgres or Elasticsearch for a searchable archive.
Step 3: Configure the connection Select the items stream with Incremental Append, schedule syncs often enough that items do not scroll off the feed between runs, and deduplicate on the link in the destination. The process is the same whether you start with Airbyte Cloud or run self-hosted Airbyte Core .
Converting a feed to CSV or JSON is a one-off version of what RSS ETL tools do continuously. The quickest routes are:
Spreadsheet: IMPORTFEED pulls items into Google Sheets, which you can then download as CSV.Python: feedparser reads the feed and Python's csv or json module writes the items out in a few lines.Scheduled exports: Airbyte can land feed items in S3 or another file destination as CSV, JSON Lines or Parquet on a schedule, so the export keeps itself up to date.Whichever route you use, keep the link and publication date as columns, since they are what you will deduplicate and sort on later.
Sending new items to email or Slack is the most common RSS automation, and it suits the workflow tools in this guide rather than warehouse connectors:
Zapier or Make: an RSS trigger followed by a Slack or email action posts each new item within minutes, depending on your plan's polling interval.n8n: the RSS Feed Trigger node can post to Slack, Microsoft Teams or email from your own server, with filters to send only matching items.Slack's RSS app: Slack's built-in RSS app can follow a feed in a channel, which is the simplest option when you need no filtering.Digests: instead of one message per item, Make or n8n can aggregate items and send one daily digest, which keeps busy channels and inboxes readable.Start with what you want to do with the items. To build a searchable, analysable archive of many feeds, use Airbyte, dlt or custom code with feedparser. To react to new items, use Zapier or Make for no-code alerts, n8n if you want to self-host, or Pipedream if you want code steps. To glance at a few feeds, IMPORTFEED in Google Sheets is enough. If you are monitoring news specifically, a news API may be a better fit; see our guide to News API ETL tools .
For a wider view of the market, see our guide to the best data integration tools .
Archive RSS feeds with Airbyte Airbyte is the open-source data connectivity platform for AI and analytics. Sync RSS feed items incrementally into the warehouse you choose, next to 700+ other sources, in Airbyte Cloud, in your own environment with Airbyte Flex, or self-hosted with Airbyte Core.
Try Airbyte Cloud free for 14 days or talk to our team .
Frequently Asked Questions (FAQs) For archiving feeds in a warehouse, Airbyte, dlt and custom code with feedparser work well. For alerts and automation, Zapier, Make, n8n and Pipedream are quicker, and Google Sheets IMPORTFEED suits watching a few feeds.
The RSS specification makes item identifiers optional, so tools often cannot tell an edited or republished item from a new one. Deduplicate on the item link in your destination.
Usually not. Most feeds show only recent items, so history has to be built by syncing regularly from the start rather than backfilling later.
4. How many feeds can one Airbyte source read? One. Airbyte's RSS source takes a single feed URL, so each publication needs its own source and connection.
RSS is free and covers any site that publishes a feed, but quality varies. A news API offers search, filtering and consistent fields across many publishers, usually for a fee.
Suggested reads News API ETL Tools
Web Scraping Tools
Elasticsearch ETL Tools
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