Best Reddit scrapers in 2026

A Reddit scraper is a tool that collects public Reddit content (posts, comments, subreddit listings, user pages) and returns it as structured data instead of a web page you read by hand. The one thing to know before you buy anything: the output you need decides the tool, because a post list, a full comment tree and a search-results export are three different jobs.

In our database, three vendors list a Reddit option on their own site: Crawlbase (a Reddit scraper inside its Crawling API), Apify (a community Reddit scraper actor) and Browse AI (a no-code robot template for Reddit search). That is a short list, and it shows how the market splits: an API you call from code, a marketplace of actors, and a point-and-click tool. The full comparison is on our Reddit scrapers ranking.

Which route is best depends on volume, budget and how much code you want to maintain. A reddit data scraper can be any of the three approaches below, and most teams end up trying two of them.

An Apify Reddit scraper is a ready-made program (an actor) that runs on the Apify platform, and in our data the Reddit one is a community actor, not made by Apify. That distinction matters: community actors are maintained by outside developers who can change inputs, change pricing or stop updating.

Apify bills platform usage plus per-actor pricing, and it gives a free monthly platform credit, so the cheapest way to evaluate is to run one subreddit through the actor and read the bill. Total cost depends on the actor you pick, which is why we do not store a single entry price for it. Before you build a pipeline on an actor, check when it was last updated and how it handles failed runs.

A reddit comment scraper is only useful if it returns nested replies with parent links and timestamps, not just the top comments visible on first load. Long threads collapse most replies behind "load more" links, so test with a thread you know has hundreds of comments and count what comes back.

Check four things on a sample: whether reply depth is preserved, whether scores and timestamps are included, whether deleted or removed comments are marked, and how the tool handles very large threads. A reddit post scraper that returns titles and links is easy; the comment side is where tools differ.

A reddit scraper github project can be enough for a small, one-off job, but expect to maintain it yourself. Open-source scrapers usually wrap the official API or parse public pages, and they break when endpoints, rate limits or page markup change.

Before you rely on one, look at the last commit date, open issues about rate limiting, and whether it handles pagination and comment trees. A reddit comment scraper chrome extension from a small developer has the same risk, plus you are giving a browser extension access to your browsing. If the data feeds a business process, the time you spend fixing a script often costs more than a month of a hosted tool.

Reddit's API is no longer a free-for-all: it has rate limits, a developer agreement and separate terms for commercial use, so the real comparison is rules and volume, not only price. We do not store Reddit's current pricing here because it changes, so read the current terms on Reddit directly before you plan around a number.

Scraping public pages avoids the API's quotas, but it does not avoid the terms. Reddit's user agreement and data terms can still apply to automated collection, and courts and platform rules differ by country. This is a description, not legal advice: if the data feeds a product, a resale or a model, ask a lawyer before you ship.

Reddit data works well for sentiment analysis and market research because people write long, candid posts and comments in topic-specific subreddits. For those uses, comments matter more than posts, and a clean export with subreddit, timestamp, score and thread ID beats a big messy dump.

Training AI models on Reddit data is a different case from reading threads for research. Reddit's data terms treat it separately from ordinary access, and privacy laws can apply to usernames and personal details inside comments. Strip identifiers you do not need, keep a record of where and when you collected, and check the current terms for your use case.

Pick by running the same sample on every candidate: one subreddit, one week of posts and 20 threads with long comment trees. Count how many threads return complete comments, then divide the bill by the number of usable results. That cost per thousand posts is the figure our table cannot give you.

Then look at the fit. If you code, a scraping API such as Crawlbase is the direct route, with a higher entry price. If you want to test cheaply, start with the free credit on Apify and see how the community actor behaves, or use Browse AI with no code. For wider options see our best scraping APIs and free scraping APIs rankings.