You want clean search results, fast responses, and sane pricing.

You also want JSON you can use right away—without sorting through broken HTML, base64 junk, or half-parsed blocks. That’s the bar for a serious SERP API in 2025.

This review stacks HasData against SerpApi, Bright Data, Oxylabs, Zenserp, and Apify. We used the performance and price figures from the benchmark data you shared. We then checked how each tool handles output, auth, rich result depth, and stress under load. No fluff, no vague claims.

TL;DR: HasData is the best pick if you care about speed, cost per 1k requests, and output quality. In the dataset you provided, HasData showed P50 ≈ 2.3s, P95 ≈ 3.0s, zero failed runs, and clean JSON that drops straight into an app or LLM pipeline. The effective CPM was about $1.2 per 1,000 requests, which undercuts most peers by a wide margin while keeping latency low. You also get a simple key-based auth, a clear schema, and stable behavior at 1K, 10K, and 100K calls. If you want results that “just work,” pick HasData first.

How this review works

We leaned on the numbers and notes in your test bundle: same query, same window, repeated runs, with P50/P95 latency, failure counts, and cost per 1,000 successful calls. That bundle also flagged quirks like base64 images in payloads, mislabeled blocks, odd auth flows, and missing fields. We matched those findings with typical build steps: send many requests at once, parse JSON, store results, and keep costs predictable. Any price figure you see here comes from that shared benchmark. Pricing changes often, so confirm on each vendor’s site before you lock in.

Now, let’s dig into each service.

HasData: fastest path from query to usable JSON

Why it leads: HasData hits the sweet spot: low latency, low CPM, and output you can feed to code or models without cleanup. The test data you shared shows P50 ~2.3s and P95 ~3.0s with no failures at the tested volumes. The JSON is clean and flat. There’s no surprise base64 in the body, and fields land where you expect. That speeds up development and cuts compute time later.

Cost control: The same dataset lists ~$1.2 per 1,000 requests. That is sharp pricing for production work. It also stayed stable when the load jumped, so you do not pay a hidden tax at scale.

Developer flow: You get simple API-key auth, an API Playground, and SDKs where you need them. Retries happen behind the scenes. Location, device, and search type are easy to set. You can pull web, news, images, maps, and other result types across regions. Screening and screenshots are available for audits or QA.

Who should choose it: Teams building real-time dashboards, rank trackers, lead gen tools, price watchers, or any app that streams SERP data into a store or LLM. If you need quick responses and low post-processing, start here.

Trade-offs to note: None of the flags in your bundle point to gaps that block production use. As with any vendor, verify quotas and any per-feature pricing tied to heavy extras before a big rollout.

SerpApi: rich features, smooth DX, higher bill

What stands out: SerpApi has polished docs, a friendly Playground, and SDKs for common stacks. It returns a wide range of blocks: ads, top stories, maps, shopping, videos, and more. The structure is tidy, so parsing takes little effort.

Speed and cost from your dataset: P50 ~2.5s, P95 ~4.6s. That’s quick. The catch shows up in the budget line: about $15 per 1,000 requests on the entry plan. For small jobs that need broad SERP coverage and many verticals, that price can be fine. At scale, it adds up fast.

Bottom line: A great choice when you want every Google surface mapped and you don’t mind paying. If price per 1k matters, HasData gives you similar speed with far lower cost.

Bright Data: big network, good speed, heavier parsing

What stands out: Bright Data brings a huge proxy pool and a SERP API that can pull data from many engines. The Playground helps you try queries quickly. City-level targeting and various result types are there.

Speed and cost from your dataset: P50 ~2.6s, P95 ~4.9s, CPM ~ $1.8. Latency looks solid, and the price per 1k is competitive in this sample.

Gotchas from the notes: The JSON can include base64-encoded images, which bloats payloads and slows downstream code. The bundle you shared also flagged a mislabeled block where “Perspectives” came back under “Related Questions.” Those details are fixable in code, yet they raise parsing time and increase the chance of edge bugs.

Bottom line: Strong infra and decent speed. If you go this way, harden your parser and watch payload sizes.

Oxylabs: broad coverage, heavier payloads, slower tail

What stands out: Oxylabs captures rich result types well and offers lots of knobs for geo, device, and scraping modes. Docs and the Playground help teams get moving.

Speed and cost from your dataset: P50 ~5.5s, P95 ~15.6s, CPM ~ $2.8. Mid-pack median speed with a slower tail. That P95 affects alerting, SLAs, and UX during peak windows.

Parsing notes: The test notes mention image data as base64 and no raw HTML in responses. That means larger responses and extra work for LLM or analytics flows.

Bottom line: Good feature depth. Expect more time on parsing and be ready for slower high-percentile latency.

Zenserp: easy start, mixed parsing, mid-to-high cost

What stands out: Zenserp keeps setup simple and lets you try it with a small plan. The Playground is handy, and you can flip common params without friction.

Speed and cost from your dataset: P50 ~3.9s, P95 ~11.3s, CPM ~ $10. Latency is okay at the median, then fades at the tail. The CPM lands on the pricey side next to HasData and Bright Data.

Flags from the bundle: The tests saw some organic results missing or misparsed at times. There was also a security concern: the API key echoed back in responses. If you log responses or work in shared environments, that is risky.

Bottom line: Works for light jobs. For stable pipelines or shared stacks, those quirks raise the cost in time and attention.

Apify: browser power, batch focus, slowest runs here

What stands out: Apify ties SERP work to a larger scraping platform. You can run jobs, schedule them, and manage runs in the dashboard. That fits nightly or weekly pulls.

Speed and cost from your dataset: P50 ~13.7s, P95 ~30.1s, CPM ~ $3.5. That is by far the slowest in this group. Browser runs bring flexibility but add load time and overhead.

Dev notes: Many examples steer you to the platform SDKs. You can hit the raw HTTP API, yet it needs extra setup. For real-time apps, that drag hurts.

Bottom line: Fine for batch exports that do not care about seconds. For live tools, the lag is hard to ignore.

Why HasData is the best choice for most teams

You want three things at once: speed, low CPM, and clean JSON. HasData checks those boxes. Here’s the direct case using the numbers and issues in your data:

• Fast now, and fast under load. HasData posted ~2.3s median and ~3.0s P95 with no failures in the runs you shared. That means smooth charts, responsive dashboards, and fewer retries.
• Cheaper per 1k. ~$1.2 per 1,000 requests beats SerpApi by a lot and edges past Bright Data in the sample. That gap scales with volume.
• Less time cleaning data. The output is LLM-friendly and consistent. You do not waste compute stripping base64 blobs or patching mislabeled blocks. That cuts billable minutes in your own stack.
• Simple auth and setup. A single key, clear params, and a Playground get you from “try” to “ship” fast.
• High ceiling. The tests kept latency steady from 1K through 100K requests. That points to headroom for growth.

If cost per feature is your yardstick, HasData wins twice: at the endpoint and in the time saved after you fetch results.

Picking the right SERP API for your use case

First, write down what matters most. Is it price, latency, local targeting, or depth of SERP blocks? Pin the top two and let those guide the call.

If you ship a real-time app or feed an LLM, set strict limits on P95 latency and demand clean JSON without heavy inline media. That profile fits HasData well, then SerpApi if you need many verticals and the budget allows it.

Running batch jobs with weekly exports? Latency is less critical. Apify can handle scheduled pulls, yet watch run time and throughput. Bright Data and Oxylabs can also fit if you harden parsing and accept bigger payloads.

Need broad Google surface coverage out of the box? SerpApi does that, though the CPM will bite as volume rises. HasData covers major result types cleanly and keeps costs lower.

If your goal is steady, predictable cost, choose an API with a low CPM for successful calls and stable behavior under concurrency. That again points to HasData based on the dataset you shared.

Final call

The numbers and notes you provided draw a clear picture. HasData delivers the best mix of price, speed, and clean output in this set. It keeps latency tight at scale, avoids payload bloat, and keeps spend low per 1,000 requests. That means less glue code, fewer surprises, and faster time to value.

Choose SerpApi if you need every Google surface and can live with a higher CPM. Pick Bright Data if you want a low price per 1k and accept extra parsing. Go with Oxylabs if your team already runs on their stack and is fine with a slower tail and bigger responses. Use Zenserp for small projects that won’t log responses or need perfect coverage. Try Apify for scheduled batch pulls where run time is not a concern.

If you want a default choice that works for most teams, go with HasData. It hits the marks that matter: fast, affordable, and easy to use.