Decodo vs Bright Data 2026: Residential Proxy Pricing Compared

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If you are choosing between Decodo vs Bright Data for residential proxies in 2026, the pricing gap is still the first thing that matters. for most scraping, SEO monitoring, ad verification, and growth research workloads, Decodo is dramatically cheaper to get into, while Bright Data still charges a premium for deeper controls, longer session persistence, and a broader data collection stack around the proxy layer. the practical question is not which one is “better” in the abstract — it is whether your workflow actually needs Bright Data’s enterprise-grade targeting and add-ons badly enough to justify paying 2x to 4x more per GB.

Pricing, at the numbers that actually affect budgets

The headline difference is simple. Decodo, formerly Smartproxy, starts around $2.20/GB on pay-as-you-go, falls to roughly $1.80/GB at 100GB/month, and lands near $1.40/GB at 500GB/month. Bright Data residential starts at $8.40/GB on PAYG, drops to about $3.50/GB at 500GB/month, and reaches roughly $2.30/GB at 2TB/month.

That is not a rounding-error difference. it changes whether residential proxies are viable for a mid-sized team.

plan level	Decodo residential	Bright Data residential
pay-as-you-go	$2.20/GB	$8.40/GB
100GB/month	~$1.80/GB	not the usual sweet spot
500GB/month	~$1.40/GB	$3.50/GB
2TB/month	custom / lower	$2.30/GB

For a concrete monthly example:

a 100GB SEO crawl on Decodo is about $180
the same 100GB on Bright Data, at PAYG-like economics, can be $840
a 500GB recurring collection job is about $700 on Decodo versus $1,750 on Bright Data
a 2TB enterprise pipeline is where Bright Data starts looking less outrageous, but it is still not the budget choice

If your use case is rank tracking, marketplace monitoring, or collecting public product data with disciplined request shaping, Bright Data’s premium is hard to defend on cost alone. if you want broader market context beyond these two, DRT’s Top Residential Proxy Providers 2026: Side-by-Side Comparison is the better starting point.

Where Bright Data still earns its premium

Bright Data is expensive, but not irrationally so. you are paying for more than IP bandwidth.

The biggest operational advantages are:

more mature enterprise controls
longer sticky sessions, up to 24 hours
stronger geo and network targeting depth
adjacent products like Scraping Browser and SERP API
better fit for teams that want one vendor for proxies plus managed extraction tools

Decodo also supports HTTP, HTTPS, SOCKS5, rotating sessions, and sticky sessions, and its dashboard is noticeably easier to get running. that matters more than vendors admit. a tool your analyst or engineer can configure in 20 minutes is often more valuable than a theoretically stronger platform that needs billing approvals, compliance review, and a week of setup friction.

There is one tradeoff worth stating clearly. Decodo’s simpler onboarding comes with fewer enterprise-ceremony controls. Bright Data is built for organizations that want centralization, policy, longer-lived sessions, and eventually a path into APIs that abstract away proxy handling entirely.

For SEO and SERP-heavy work, that last point matters. Bright Data’s managed stack can be attractive if you want to move from raw proxy management into higher-level extraction. that is also why DRT’s pillar guide, Bright Data Pricing 2026: Residential, ISP, Mobile — What Each Plan Actually Costs, is useful to read before procurement conversations, because the residential line item is only part of the real spend.

Pool size, targeting, and session behavior

On paper, Bright Data has the larger residential network. Decodo claims roughly 115M IPs, while Bright Data is typically cited at 150M+ IPs in audited residential pool counts. DRT broke that out in Bright Data Residential Proxy Pool Size 2026: Real Numbers Audited, and the short version is that Bright Data still leads on raw scale.

But pool size is one of the most abused proxy metrics in the market. the better question is whether you can get stable, relevant exits for your target geography and session model.

What matters more than the headline IP count

geo resolution: Bright Data is still the more granular choice in real workflows, especially for city and ASN-level controls, and broader carrier-level targeting across its platform stack
session persistence: Decodo sticky sessions are usually treated as 30 minutes max in common self-serve usage, while Bright Data can hold sessions for up to 24 hours
onboarding friction: Decodo has no minimum spend, while Bright Data often pushes you toward a $500 deposit or a custom contract once you move into enterprise-style usage
tooling depth: Bright Data gives you a stronger upgrade path into managed scraping products, Decodo keeps the proxy layer simpler

If you need to look like one consistent user for cart flows, logged-in QA, or long browser sessions, Bright Data’s session ceiling is not a cosmetic feature. it can reduce session churn and failure handling in your scraper. if you just need steady rotation across public pages, Decodo’s session model is usually enough.

What implementation looks like in practice

For engineers, neither product is hard to wire up. both support standard authenticated proxies over HTTP, HTTPS, and SOCKS5. the real difference appears after the first successful request, when you start managing retries, country routing, sticky state, and failure budgets.

A minimal Python example with Bright Data-style proxy auth looks like this:

import requests

proxy_user = "brd-customer-123456-zone-resi-country-us-session-abc123"
proxy_pass = "your_zone_password"
proxy_host = "brd.superproxy.io"
proxy_port = 33335

proxies = {
    "http": f"http://{proxy_user}:{proxy_pass}@{proxy_host}:{proxy_port}",
    "https": f"http://{proxy_user}:{proxy_pass}@{proxy_host}:{proxy_port}",
}

resp = requests.get(
    "https://httpbin.org/ip",
    proxies=proxies,
    timeout=30,
)

print(resp.status_code, resp.text)

That config is straightforward. the hard part is cost control. residential proxy bills usually explode because teams do one or more of the following:

fetch full pages when a lightweight endpoint or cached source would do
retry too aggressively on soft blocks
use residential IPs for targets that are perfectly accessible via datacenter proxies
keep browser sessions open longer than the task requires

That is why a mixed-stack approach often beats picking one residential provider for everything. for easier targets, pair residential with datacenter capacity, and use residential only where block rates justify it. DRT’s Best Datacenter Proxy Providers with Geo-Targeting 2026: 7 Tested covers the cheaper side of that stack design.

Who should pick which provider

If choosing for different teams, the split would be pretty clean.

pick Decodo if:

you want the lower-cost default for scraping public web data
you have engineers or analysts who need a clean dashboard and fast onboarding
you do not want procurement friction or minimum-spend pressure
your sessions are short to medium length
budget efficiency matters more than max configurability

pick Bright Data if:

you need long-lived sticky sessions
you care about the deepest targeting controls and enterprise workflows
you expect to use Scraping Browser or SERP API, not just raw proxies
you can absorb higher minimum commitments
your blocker is not setup speed, it is reliability under tougher anti-bot conditions

There is also a third category of buyer: teams that should not use either first. if your monthly budget is tight and your targets are not especially hardened, you may get better ROI from lower-cost residential vendors. that is the angle in Webshare vs Proxy-Cheap vs IPRoyal: Budget Residential Proxies 2026.

Bottom line

For most engineers, SEO teams, and growth analysts, Decodo wins the price-to-utility comparison in 2026. Bright Data is the stronger enterprise platform, but you should only pay that premium if you truly need longer sessions, tighter targeting, or its managed scraping products. if you are comparing proxy vendors for a real workflow, DRT at dataresearchtools.com is the right place to benchmark the actual tradeoffs instead of marketing claims.