Software Alternatives, Accelerators & Startups

SocialFetch.dev VS Qubole

Compare SocialFetch.dev VS Qubole and see what are their differences

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SocialFetch.dev logo SocialFetch.dev

Social media scraping API for public profiles, posts, comments, videos, transcripts, and metrics from TikTok, Instagram, YouTube, X, LinkedIn, and more. Pay-as-you-go credits, 100 free to start.

Qubole logo Qubole

Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.
  • SocialFetch.dev Landing page
    Landing page //
    2026-06-17
  • SocialFetch.dev Test our API in the playground.
    Test our API in the playground. //
    2026-06-17

Social Fetch is the social media data API for teams that need to ship features, not maintain scrapers.

Every major platform changes its DOM, blocks proxies, and breaks homegrown integrations. Social Fetch handles that infrastructure โ€” headless browsers, rate limits, normalization โ€” so you get clean, live JSON back on every request. No stale cache. No per-platform parsers in your codebase.

What you can fetch: profiles and follower data, posts and reels, comments and threads, video transcripts, hashtag/keyword search, ad library intelligence, and engagement metrics โ€” across TikTok, Instagram, YouTube, X, LinkedIn, Facebook, Reddit, Threads, GitHub, Spotify, and more.

Built for: creator tools, marketing analytics, brand safety and impersonation detection, competitive intelligence, enrichment pipelines, monitoring dashboards, and AI agent workflows. Integrate with cURL, Python, Node, our official TypeScript SDK, or our MCP server for Cursor and Claude.

Pricing: pay-as-you-go credits that never expire. No monthly subscription. Start with 100 free credits โ€” no credit card required.

  • Qubole Landing page
    Landing page //
    2023-06-22

SocialFetch.dev

$ Details
freemium $9.0 (Pay-as-you-go credits, never expire)
Platforms
Web
Release Date
2024 January
Startup details
Country
United Kingdom
Founder(s)
Luke Askew
Employees
1 - 9

SocialFetch.dev features and specs

  • API
    REST API with unified JSON schema across 20+ social platforms
  • Data Scraping
    TikTok, Instagram, YouTube, X, LinkedIn, Facebook, Reddit, Threads, and 15+ more
  • Pricing Model
    Pay-as-you-go credits. No subscription. 100 free to start.

Qubole features and specs

  • Scalability
    Qubole allows seamless scalability, adjusting resources automatically based on workload, which facilitates efficient handling of large data sets and peaks in demand.
  • Multi-cloud Support
    Qubole offers support for multiple cloud providers, including AWS, Azure, and Google Cloud, giving users flexibility and freedom to choose or shift between cloud services.
  • Unified Interface
    The platform provides a unified interface for diverse data processing engines such as Apache Spark, Hadoop, Presto, and Hive, simplifying the management of big data operations.
  • Cost Management
    Qubole includes features for cost management and optimization, such as intelligent spot instance usage, which can reduce operational costs significantly.
  • Data Security
    Qubole offers robust security features, including encryption, access controls, and compliance with various regulations, which assists in maintaining data privacy and protection.
  • Integration Capabilities
    The platform supports integration with many other tools and services, which enables a streamlined pipeline for data extraction, transformation, loading (ETL), and analysis.

Possible disadvantages of Qubole

  • Complex Setup
    For users unfamiliar with big data infrastructure and cloud platforms, the initial setup and configuration of Qubole may present a steep learning curve.
  • Cost Overruns
    Without careful management and monitoring, the automatic scaling and utilization of cloud resources can lead to unexpected and potentially high costs.
  • Dependency on Cloud Availability
    As a cloud-based platform, Qubole's performance and availability are contingent on the underlying cloud provider, which means service disruptions or performance issues in the cloud can affect Quboleโ€™s operations.
  • Vendor Lock-in
    While Qubole supports multiple clouds, migrating away from the platform to another big data solution can be complex due to dependency on Qubole-specific configurations and optimizations.
  • Support and Documentation
    Some users have reported that the quality and depth of support and documentation provided by Qubole can vary, which may affect troubleshooting and learning.
  • User Interface
    While the interface is comprehensive, some users may find it less intuitive compared to other platforms, which can hinder ease of use and efficiency.

Analysis of SocialFetch.dev

Overall verdict

  • I don't have verified information about SocialFetch.dev in my training data, so I can't confirm its features, reliability, pricing, or legitimacy. Based on the name, it appears to be a tool related to fetching or scraping social media data/content, but I cannot verify its quality, safety, or whether it's an active, reputable service.

Why this product is good

  • Unable to verify specific features or capabilities of this service
  • No confirmed data on user reviews, uptime, or customer support quality
  • Cannot confirm compliance with social media platforms' terms of service (data scraping tools often violate platform ToS)
  • No verifiable information on pricing, security practices, or company legitimacy

Recommended for

  • Before using this service, verify its legitimacy through independent reviews, check if it complies with relevant platform APIs and terms of service
  • Research whether the service has a transparent privacy policy and data handling practices
  • Confirm the company's reputation through third-party sources like Trustpilot, Reddit, or G2
  • Consult with a technical or legal advisor if using it for business purposes involving social media data extraction

Analysis of Qubole

Overall verdict

  • Qubole is generally considered a good platform for managing big data workloads, especially for businesses that seek flexibility and efficiency in processing and analyzing large-scale datasets. Its ability to automate and optimize workflows can lead to significant productivity gains and cost savings.

Why this product is good

  • Qubole is a cloud-based data platform that is designed to simplify and optimize big data processing. It allows data teams to manage and analyze large datasets efficiently by providing a unified interface for various data processing engines, including Apache Spark, Hive, and Presto. Its scalability, ease of integration with multiple cloud providers, automated data workflows, and support for machine learning models make it a valuable tool for organizations handling extensive data operations.

Recommended for

  • Data engineers and data scientists who need a robust platform for processing large volumes of data.
  • Organizations looking to leverage cloud-based solutions for big data processing and analytics.
  • Companies that want to integrate multiple data processing engines under a single management platform.
  • Businesses that require flexibility in scaling their data infrastructure in response to changing workloads.

SocialFetch.dev videos

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Qubole videos

Fast and Cost Effective Machine Learning Deployment with S3, Qubole, and Spark

More videos:

  • Review - Migrating Big Data to the Cloud: WANdisco, GigaOM and Qubole
  • Review - Democratizing Data with Qubole

Category Popularity

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Questions & Answers

As answered by people managing SocialFetch.dev and Qubole.

What makes your product unique?

SocialFetch.dev's answer

Social Fetch provides a unified REST API that lets developers collect public data from 20+ social platforms โ€” TikTok, Instagram, YouTube, X, LinkedIn, Reddit, Facebook, Threads, and more โ€” using a single consistent JSON schema. There is no need to learn or maintain separate APIs for each network. Credits never expire, and you only pay for what you use, making it ideal for both prototyping and production-scale data pipelines.

Why should a person choose your product over its competitors?

SocialFetch.dev's answer

Unlike solutions that require you to set up and maintain separate API integrations for each platform, Social Fetch gives you one API key and one consistent schema across all supported networks. You get the same response structure whether you are fetching TikTok videos, Instagram posts, or YouTube channels. The pay-as-you-go model means no wasted monthly spend on idle subscriptions, and credits never expire so there is no pressure to use them up.

How would you describe the primary audience of your product?

SocialFetch.dev's answer

Social Fetch is primarily used by developers, data engineers, and growth marketers who need programmatic access to social media data without building and maintaining individual platform integrations. Common use cases include social analytics tools, influencer research platforms, content aggregation pipelines, brand monitoring dashboards, and AI training datasets that require large-scale social content.

What's the story behind your product?

SocialFetch.dev's answer

Social Fetch was founded by Luke Askew, a developer who repeatedly ran into the same problem while building social analytics tools: every platform had a different API, different authentication flows, different rate limits, and different response shapes. Building and maintaining integrations for even a handful of platforms was a significant ongoing burden. Social Fetch was created to solve this by acting as a single abstraction layer, so developers can focus on what they are building rather than on the plumbing beneath it.

Which are the primary technologies used for building your product?

SocialFetch.dev's answer

Social Fetch is built on Next.js and TypeScript, deployed on Vercel. The API layer is serverless and runs on edge infrastructure for low latency globally. Data is processed and stored using cloud-native services, and the platform uses tRPC for type-safe internal APIs. The codebase is a TypeScript monorepo, enabling shared types between the API, frontend, and internal tooling.

Who are some of the biggest customers of your product?

SocialFetch.dev's answer

Social Fetch is currently used by early-stage startups, independent developers, and small analytics teams. As a newer product launched in 2024, we are still growing our customer base. If you are interested in using Social Fetch or would like to be featured here, please reach out at hello@socialfetch.dev.

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What are some alternatives?

When comparing SocialFetch.dev and Qubole, you can also consider the following products

API Direct - A pay-as-you-go social media API. Search real-time data across multiple social platforms through one standardized API. No monthly fees or commitments โ€” just pay per request.

MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming

Apify Python SDK - Build and manage web scraping Actors in the cloud.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Simple Scraper - Extract data from any website in seconds โ€” download instantly, scrape in the cloud, or create an API.

Snowflake - Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.