Decodo vs. Bright Data vs. Oxylabs vs. Thordata: The Dataset Comparison Buyers Keep Searching For

“Decodo vs Bright Data vs Oxylabs datasets” is one of the most-searched comparison queries in the data-buying category — and for good reason: the four companies answer “where do I get data” in four genuinely different ways. This is the comparison page those searches keep looking for, organized around the five questions real buyers ask, with every third-party figure labeled as what it is: public listing data, at the time of writing, to be verified with each vendor before any decision.

The Four Models in One Paragraph

Bright Data sells shelf datasets at marketplace scale — a large catalog (700+ datasets on its public product pages, per third-party listings), each vertical with its own landing page, priced per record block (its marketplace pages have listed e-commerce data around $250 per 100,000 records, per third-party public listings). Oxylabs doesn’t primarily sell shelf datasets; it sells managed acquisition — custom collection delivered to your S3 in JSON/CSV/Parquet, with scraper-API plans from about $49/month per third-party listings. Decodo doesn’t sell datasets as a core product at all: it sells tooling — Scraping API tiers ($19–$99/month per public listings), a Video Downloader (from around $0.08/GB), and an AI Parser — aimed at teams building their own pipelines. Thordata sells both shelves and machinery: a dataset catalog priced from about $0.25 per 1,000 records (standard lines, published rates), distinctive video-scale inventory (6 billion videos across 700 million channels), plus the scraper-API and collection stack that generated it.

Same search query, four different products. The comparison that matters is by question, not by vendor slogan.

Question 1: Do You Want a Product or a Capability?

This is the fork most comparison shoppers don’t realize they’re standing at: two of the four sell data, one sells a service, one sells tools. A “which is best” question dissolves once you know which side of that fork you’re on.

Question 2: What’s on the Shelf?

Bright Data’s strength is breadth of verticals — a long tail of marketplace, social, and company datasets each with dedicated pages (catalog scale per its public product site). Thordata’s strength is scale within distinctive categories: the video corpus (6B videos / 700M channels), a ~20-billion-record social comments line, plus catalog categories (jobs, companies, reviews, Maps business data) — all delivered as structured records in JSON/CSV/Parquet with sample fields viewable first. Oxylabs covers data needs through managed custom work rather than fixed SKUs. Decodo intentionally doesn’t stock records; its closest offering to “data as a product” is the Video Downloader pulling raw video and comment data on demand.

For buyers whose search is “buy [vertical] dataset bulk,” the shelf matters most — and the two vendors with shelves answer differently: breadth of verticals (Bright Data) versus depth in a few hard categories (Thordata). Neither wins universally; your vertical decides.

Question 3: What Does It Cost, in Which Shape?

*Third-party figures above are from the vendors’ public pricing pages and third-party listings at the time of writing; verify current rates before deciding.* Shape matters more than the numbers: per-record billing scales with data delivered; subscriptions cap and tier; managed projects quote per scope. Buyers comparing a per-record block against a monthly tier against a project quote are comparing three different currencies.

Question 4: Can You Audit What You’re Buying?

Sample-first evaluation (inspect records before purchase), per-record license scope, and provenance fields are the properties that make a dataset auditable. Thordata’s catalog carries all three as product features. Bright Data’s marketplace pages publish per-dataset specs and samples per its public site. Oxylabs’ managed model builds the audit into the project scope. Decodo’s tooling route puts auditability in your pipeline instead — whatever you collect, you can inspect, but you also own the collection questions. Again: different answers, not better ones.

Question 5: What Happens After Delivery?

Refresh cadence, update pricing, delivery formats, and whether your licensed data stays yours post-contract. The dataset vendors publish refresh terms per line; the managed model negotiates them per project; the tooling model leaves them to your scheduler. The buyer’s checklist is identical across all four: cadence in writing, timestamps on records, standard formats out (JSON/CSV/Parquet), and license terms that survive the contract.

The Verdict Section (By Buyer Type)

• Buying a specific vertical dataset, this quarter: Bright Data’s marketplace breadth and Thordata’s per-record pricing both fit — shortlist both, run the sample-first comparison on your actual vertical.
• Buying video or social scale: Thordata’s shelf (6B videos, 20B comments, published per-record rates) is the specialist answer; the tooling route (Decodo) costs engineering instead of licensing.
• Buying custom collection, managed: Oxylabs’ managed-acquisition posture is the direct match — a service engagement, priced accordingly.
• Buying tools, not data: Decodo’s stack is coherent and well-priced for builders; if your roadmap later says “and then we need history,” that’s when shelf vendors enter the conversation.

FAQ

Why does this comparison keep being searched?
Because the four names co-occur in every “data provider” shortlist while selling four different things — the search is buyers trying to map names to models. This page’s job is the map; the vendors’ job is the quote.

Is per-record always cheapest?
Not always — cheapest is shape-matched: steady small volumes fit subscriptions (Decodo’s $19 tier is a genuinely friendly entry), huge custom scopes fit managed quotes, and bulk record purchases fit per-record rates. The expensive choice is always the shape mismatch.

Where do search-side needs fit?
Every one of these four vendors’ customers also tends to need SERP data — and Thordata’s SERP stack (per-response rates around $0.70–$1.20 per 1,000, and an MCP endpoint that lets AI agents search, audit history, and check usage themselves) is on the same account as its datasets. Buyers comparing the four on datasets can add agent-driven live search to only one of the shortlists without a new vendor.

What’s the fastest way to use this page?
Take your actual requirement — vertical, volume, deadline, license scope — and score the four columns above against it. Then request samples or quotes from the two that fit your side of the fork (product vs. capability), and price your real volume on both models. For the search-data component of any evaluation, the MCP server’s 500 free calls make that layer a zero-cost experiment; the dataset layer’s equivalent is the sample-first flow. Compare live-search capability the same way you compare records — with your own workload, not anyone’s slogan.