Bright Data Reviews

1. Sam Mitchell

   · Owner at KittenProperties · over 2 years ago
   Mixed feelings

   We used their DC proxies and Residential proxies. Resi proxies were having quite low success rate. We had to use resi solution from other proxy providers. Unblocker didn't work well either also it was way too expensive.

   🏁 Competitors: Decodo, NetNut.io

   👍 Pros:    Cheap dc proxies

   👎 Cons:    Quite expensive|Residential proxies are worse than competitiors

GraphQL Cache Reviews

Bright Data mentions (45)

• Precursor

  Happy to offer a counter of some great products for anti-bot defeat: https://brightdata.com/ https://www.zenrows.com/ https://www.capsolver.com/ https://scrapfly.io/ hundreds of millions of residential ips, human browser fingerprints, custom browser binaries, auto solve of turnstyle, recaptcha v3, kasada, datadome, AWS WAF, etc if they come up. - Source: Hacker News / about 1 month ago

• Best Web Scraping Tools in 2026: A Hands-On Comparison of the Top 10

  The best web scraping tools 2026 leaderboard hasn't changed; the gap has narrowed. Bright Data remains the safest bet for any team that wants to spend time on the data, not on the scraping. The 660-scraper library, 400M-IP network, pay-per-success pricing and unlimited concurrency are still uncontested at the high end. - Source: dev.to / 3 months ago

• The Economics of Web Scraping: How Consultancies Price Data Extraction and Manage Scope Creep

  Infrastructure Pass-Through (OpEx) Data extraction at scale is infrastructure-heavy. Bypassing modern Web Application Firewalls (WAFs) requires high-quality residential proxies, CAPTCHA solvers, and substantial browser-automation compute resources. Services like Bright Data charge significantly by the gigabyte for premium residential IPs. These variable infrastructure costs must be passed directly to the client,... - Source: dev.to / 4 months ago

• LinkedIn Scraping Is Dead: 5 Legal, ToS-Safe Alternatives That Actually Work in 2026

  Bright Data has successfully defended web scraping in U.S. Courts and offers LinkedIn datasets pre-collected and ready to download. LinkedIn profile data on their dataset marketplace runs around $250 per 100,000 records. The freshness caveat is real: bulk datasets are snapshots, not real-time. If you need current job titles on a rolling basis, you're better with an enrichment API than a one-time dataset pull.... - Source: dev.to / 4 months ago

• Building a Live AI Market Research Terminal: How Bright Data and Convex Replace Polling With Real-Time Everything

  Bright Data built an open-source demo that solves this. It's called the Signal Terminal, a financial research tool built around that problem. - Source: dev.to / 5 months ago

GraphQL Cache mentions (4)

• What are the Differences between GQL and REST?

  'id' data type and field to help support caching: https://graphql.org/learn/caching/. Source: over 3 years ago

• GraphQL Is a Trap?

  > Take a look at this. I repeat: client-side caching is not a problem, even with GraphQL. The technical problems regarding GraphQL's blockers to caching lies in server-side caching. For server-side caching, the only answer that GraphQL offers is to use primary keys, hand-wave a lot, and hope that your GraphQL implementation did some sort of optimization to handle that corner case by caching results. Don't take my... - Source: Hacker News / over 4 years ago

• GraphQL Is a Trap?

  > Checkout Relay.js: https://relay.dev/ Relay is a GraphQL client. That's the irrelevant side of caching, because that can be trivially implemented by an intern, specially given GraphQL's official copout of caching based on primary keys [1], and doesn't have any meaningful impact on the client's resources. The relevant side of caching is server-side caching: the bits of your system that allow it to fulfill... - Source: Hacker News / over 4 years ago

• Designing a URL-based query syntax for GraphQL

  This is clever! Can anyone help me understand how this lines up with the original value proposition of GraphQL? I was under the impression that the Big Idea behind GraphQL was, amongst other things, client-side caching[1]. I’m probably missing some nuance here, so bear with me: if your GraphQL client is caching properly, then what would this syntax give a developer that a URL query parameter parser couldn’t? [1]... - Source: Hacker News / about 5 years ago