We extract app metadata, download metrics, expert reviews, and license types from Softonic. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for App Listings objects from softonic.com. All fields typed and schema-versioned.
"app_id": "winrar", "title": "WinRAR", "developer": "RARLAB", "os_platform": "Windows", "license_type": "Trial version", "rating": 4.8, "download_count": 5429104, "current_version": "6.24"
| # | app_id | title | developer | os_platform | license_type | rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for User Reviews objects from softonic.com. All fields typed and schema-versioned.
"review_id": "rev_982341", "app_id": "winrar", "username": "tech_user_99", "rating": 5, "review_date": "2023-10-14", "review_text": "Essential utility for any new PC build.", "helpful_votes": 34, "os_version": "Windows 11"
| # | review_id | app_id | username | rating | review_date | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Expert Reviews objects from softonic.com. All fields typed and schema-versioned.
"expert_name": "Elena Santos", "score": 9.0, "pros": "['High compression ratio', 'Encryption support']", "cons": "['Outdated interface']", "verdict": "Still the gold standard for file compression.", "review_date": "2023-01-12", "app_id": "winrar"
| # | expert_name | score | pros | cons | verdict | review_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Version History objects from softonic.com. All fields typed and schema-versioned.
"app_id": "winrar", "version_number": "6.23", "release_date": "2023-08-02", "changelog": "Security patch for CVE-2023-40477.", "file_size": "3.4 MB", "os_target": "Windows 64-bit", "download_url_stub": "/download/version/6.23"
| # | app_id | version_number | release_date | changelog | file_size | os_target |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Search Results objects from softonic.com. All fields typed and schema-versioned.
"keyword": "video editor", "rank_position": 1, "app_id": "capcut", "title": "CapCut", "snippet": "Free versatile video editor", "rating": 4.6, "license_type": "Free", "platform": "Windows"
| # | keyword | rank_position | app_id | title | snippet | rating |
|---|---|---|---|---|---|---|
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Our Softonic scraper navigates ad-heavy DOMs, geo-redirects, and pagination limits to extract clean software metadata, historical version logs, and user sentiment across all device categories.
Extract titles, developer names, file sizes, language availability, and detailed descriptions across millions of software listings.
Categorise software by license type: Free, Trial, Open Source, or Paid, including subscription indicators.
Monitor changelogs, release dates, and legacy version availability for cybersecurity and compatibility research.
Capture user ratings, text reviews, and expert editorial scores to gauge software reputation over time.
Extract embedded VirusTotal scan reports and safety badges displayed on the application download pages.
Link Windows, Mac, Android, and iOS versions of the same application using Softonic's internal category structures.
Map 'Users also downloaded' and 'Alternative to' sections to build competitor graphs and market share models.
Bypass regional redirects using localised residential proxies to extract software availability specific to distinct markets.
Run daily pipelines that only output new app listings, version updates, or fresh reviews to minimise processing overhead.
Brief in. Clean data out.
Provide categories, OS platforms, or specific developer names. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, handle geo-routing, and bypass ad-injections for softonic.com.
Schema validation, null-rate checks, and version-outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Software portals are notoriously difficult to scrape due to legacy DOM structures, aggressive ad scripts, and regional content variations. Here is how we build resilient pipelines.
Softonic pages are laden with third-party ad networks and tracking scripts that slow down rendering and alter DOM structures. We intercept and block non-essential network requests at the browser level, isolating the core application metadata.
Softonic routes traffic to different subdomains (e.g., en.softonic.com, es.softonic.com) based on IP geolocation. We use targeted residential proxies to maintain persistent regional sessions and extract accurate, locale-specific software catalogues.
Due to decades of legacy content, app pages vary wildly in structure. Our parsers use cascading fallback selectors, checking modern JSON-LD schemas first, then specific CSS classes, and finally regex patterns on raw HTML to ensure high field completion rates.
Softonic limits deep pagination on broad category pages. We bypass this by spidering through granular sub-categories, tags, and developer pages to ensure complete catalogue extraction without hitting arbitrary display limits.
Software metadata changes infrequently compared to eCommerce pricing. We hash the payload of each application record. Subsequent crawls only emit data when a new version is released, a license changes, or new reviews appear.
Track software categories to identify trending applications, dominant platforms, and shifts in licensing models from paid to freemium.
Monitor application version histories, SHA hashes, and embedded VirusTotal flags to track the distribution of potentially unwanted programs (PUPs).
Software developers monitor alternative app suggestions and user sentiment to identify feature gaps in competing products.
Analyse highly-ranked software descriptions and category structures to optimise external app store and search engine presence.
Map the ecosystem of legacy Windows utilities vs modern SaaS wrappers to understand long-tail software usage.
Ingest millions of expert and user reviews to train natural language processing models on software-specific terminology and sentiment.
"Softonic catalogues decades of software history and user sentiment across multiple platforms, but extracting it requires navigating heavy ad-injected DOMs and aggressive geo-routing."
Scraping software portals at scale means dealing with inconsistent legacy layouts, dynamic JavaScript components, and regional redirects. DataFlirt manages the residential proxy rotation and DOM parsing logic so your team can focus on analysing app trends and update cycles, rather than maintaining fragile selectors.
Everything supported by our softonic.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and deduplication. Playwright handles JavaScript rendering and ad-script blocking. Combined via scrapy-playwright middleware.
We maintain pools of residential proxies to bypass aggressive geo-routing, ensuring we scrape the correct regional subdomain consistently.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About softonic.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Softonic is generally permissible under applicable law. DataFlirt targets only public, non-authenticated app metadata, reviews, and version histories. We do not extract personal user data or download proprietary binary files. Clients should review Softonic's ToS and consult legal counsel for specific use cases.
We use network-level request interception in Playwright to block third-party ad networks, tracking pixels, and heavy media assets. This stabilises the DOM for reliable parsing and significantly reduces bandwidth and execution time.
Yes. Every pipeline run produces timestamped snapshots. We maintain a state index of application versions and only emit new records when a version number changes, a new changelog is posted, or the license type updates.
Yes. We traverse the category trees for Windows, Mac, Android, iOS, and web applications, mapping cross-platform alternatives where Softonic links them.
Yes. We capture the VirusTotal integration metrics displayed on the app pages, including the number of security vendors that flagged the file and the overall safety rating.
Our smallest packages start at a defined category or developer list with weekly delivery. For full catalogue extractions, we price based on volume and delivery frequency. Contact us with your use case for a scoped quote.
Absolutely. We provide a sample run of up to 1,000 app listings or specific category trees as part of the pre-engagement scoping process, allowing you to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a targeted list of competitor applications or a continuous feed of software updates across multiple operating systems, we scope, build, and operate the pipeline. Tell us what you need.
