Software Alternatives & Startups

Sweep VS Dataiku

Compare Sweep VS Dataiku and see what are their differences

Sweep

One search across several stores, price alerts that arrive while the deal is live, and real price history so you can tell a discount from a sticker.

Rating
0 reviews
Pricing
Freemium Free trial $5.99 / Monthly (Pro)
Dataiku

Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.

Rating
0 reviews
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Which is more popular?

Developer Tools popularity
100% vs 0%
alternatives listed
5 vs 177

Base details

Website, pricing, platforms and company facts side by side.

Sweep
Dataiku
Website sweepshopping.com dataiku.com
Pricing
Freemium Free trial $5.99 / Monthly (Pro) Official pricing
Company — Startup from the United States · 500 - 999 employees · 2013
Listed in

Features and specs

What each product offers, as listed by its team.

Sweep 5 features
Dataiku 6 features
  • Group Buying Deals
    Sweep allows users to combine purchasing power with others to unlock discounts on products, potentially leading to significant savings compared to shopping alone.
  • Social Shopping Experience
    The platform incorporates social elements that let users shop with friends or a community, making the experience more interactive and enjoyable than traditional solo online shopping.
  • Discovery of New Products
    Sweep can help users discover new brands and products through curated deals and community recommendations, expanding shopping options beyond typical retail search.
  • Potential Cost Savings
    By leveraging collective buying power, users may access lower prices or exclusive deals that wouldn't be available through standard retail channels.
  • Modern, User-Friendly Interface
    The platform is designed with a contemporary interface aimed at making the group shopping and deal-finding process intuitive and accessible.
  • User-Friendly Interface
    Dataiku offers an intuitive and easy-to-navigate visual interface that allows users of all technical backgrounds to create, manage, and deploy data projects without needing extensive coding knowledge.
  • Collaborative Environment
    The platform supports collaborative work, enabling data scientists, engineers, and analysts to work together on the same projects seamlessly, sharing insights and models easily.
  • End-to-End Workflow
    Dataiku provides tools that cover the entire data pipeline, from data preparation and cleaning to model building, deployment, and monitoring, making it a comprehensive solution for data teams.
  • Integrations and Extensibility
    The platform integrates with many data storage systems, machine learning libraries, and cloud services, allowing users to leverage existing tools and infrastructure.
  • Automation Capabilities
    Dataiku offers automation features such as scheduling, automation scenarios, and machine learning model monitoring, which can significantly enhance productivity and efficiency.
  • Rich Documentation and Support
    Dataiku provides extensive documentation, tutorials, and a strong support community to help users navigate the platform and troubleshoot issues.

Possible disadvantages

  • Pricing
    Dataiku can be expensive, particularly for small businesses and startups. The cost may be a barrier to entry for organizations with limited budgets.
  • Resource Intensive
    The platform can be resource-hungry, requiring significant computing power, which may necessitate additional investments in hardware or cloud services.
  • Learning Curve for Advanced Features
    Although the basic interface is user-friendly, mastering advanced features and customizations can require a steep learning curve and significant training.
  • Limited Offline Capabilities
    Dataiku relies heavily on cloud services for many of its functionalities. This dependence might be restrictive in environments with limited or no internet access.
  • Custom Model Flexibility
    While Dataiku supports many machine learning frameworks, the process of integrating custom or niche models can be cumbersome compared to using those frameworks directly.
  • Dependency on Ecosystem
    The seamless experience of Dataiku often relies on the broader cloud and data ecosystem. Changes or issues in integrated services can impact its performance and reliability.

Videos

Walkthroughs and reviews on video.

Sweep 0 videos + Add
Dataiku 3 videos + Add

No Sweep videos yet. You could help us improve this page by suggesting one.

AutoML with Dataiku: And End-to-End Demo

More videos

  • - Dataiku: For Everyone in the Data-Powered Organization
  • - Dataiku DSS Tutorial 101: Your very first steps

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Sweep
Dataiku
100% 100%
0% 0%
100% 100%
0% 0%
0% 0%
100% 100%

Questions & Answers

As answered by people managing Sweep and Dataiku.

What makes your product unique?

Sweep's answer

-Sweep keeps its own price history, so it can tell you when a "40% off" badge is sitting on the price something has been all month -It searches five stores at once — Amazon, Walmart, Best Buy, eBay and Etsy — rather than one -No AI anywhere in the price path. Every number is read from the store's listing, never predicted. When a store doesn't publish something, the app leaves a gap and names the store instead of filling it -It's funded by subscriptions, not affiliate commission, so it has no reason to talk you into buying

Why should a person choose your product over its competitors?

Sweep's answer

-CamelCamelCamel and Keepa track price history, but only on Amazon and only on the web. Honey, Rakuten and Karma cover more stores but never tell you whether a discount is real — they earn commission when you buy, so "this sale is fake" is a sentence that costs them money.

-Sweep is the overlap: price history across five stores, with an actual verdict rather than a chart to interpret. It gets paid by subscription, so it can afford to tell you not to buy.

How would you describe the primary audience of your product?

Sweep's answer

People who shop online and don't trust sale prices. Deal hunters, budget shoppers, and anyone who has bought something in a sale and later found out it had been that price all along. US-based, Android, skewing younger.

What's the story behind your product?

Sweep's answer

-I'm Jude, I'm 16, and I got annoyed at a "40% off" badge. The shop sets the original price and the shop sets the discount, so you're taking their word for both and there's usually no way to check. -So I built something that keeps its own record of what things cost. Everything else in the app grew around that one idea. I wrote all of it — the app, the servers, the scrapers, at weekends and in the evenings.

Which are the primary technologies used for building your product?

Sweep's answer

-React Native and Expo (TypeScript) -Fastify on Node.js -PostgreSQL with Prisma -Supabase for auth, Railway for hosting -RevenueCat for subscriptions, Sentry for error tracking

User comments

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Reviews and articles

External articles and on-site reviews we used to compare the two products.

Sweep no reviews yet
Dataiku no reviews yet

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