Software Alternatives, Accelerators & Startups

Amazon Machine Learning VS Grapple

Compare Amazon Machine Learning VS Grapple and see what are their differences

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Amazon Machine Learning logo Amazon Machine Learning

Machine learning made easy for developers of any skill level

Grapple logo Grapple

Do-It-Yourself Data Analytics & Business Intelligence, Powered by AI
Visit Website
  • Amazon Machine Learning Landing page
    Landing page //
    2023-03-13
  • Grapple features
    features //
    2025-06-26
  • Grapple consolidate your business data
    consolidate your business data //
    2025-06-26

Grapple

$ Details
freemium $99 / Monthly (Per Editor, Unlimited Viewers)
Platforms
Web Google Chrome Safari Firefox
Release Date
2025 May
Startup details
Country
United States
State
Nebraska
City
Omaha
Founder(s)
Jack Sellwood
Employees
1 - 9

Amazon Machine Learning features and specs

  • Scalability
    Amazon Machine Learning can handle increased workloads easily without significant changes in the infrastructure, making it ideal for growing businesses.
  • Integration with AWS
    Seamlessly integrates with other AWS services like S3, EC2, and Lambda, simplifying data storage, processing, and deployment.
  • Ease of Use
    User-friendly AWS Management Console and APIs make it easier for developers to build, train, and deploy machine learning models without needing deep ML expertise.
  • Performance
    Offers high-performance computing capabilities that can accelerate the training and inference processes for machine learning models.
  • Cost-Effective
    Pay-as-you-go pricing model ensures that you only pay for what you use, making it a cost-effective solution for various ML needs.
  • Prebuilt AI Services
    Provides prebuilt, ready-to-use AI services like Amazon Rekognition, Amazon Comprehend, and Amazon Polly, which simplify the implementation of complex ML solutions.

Possible disadvantages of Amazon Machine Learning

  • Complexity
    While the service is designed to be user-friendly, the underlying complexity of Machine Learning algorithms and models can be a barrier for novice users.
  • Vendor Lock-In
    Using Amazon Machine Learning extensively may lead to dependency on AWS services, making it difficult to switch providers or integrate with non-AWS services in the future.
  • Cost Management
    Although pay-as-you-go is cost-effective, if not managed properly, costs can quickly escalate especially with extensive use and large-scale data processing.
  • Limited Customization
    Prebuilt models and services may lack the level of customization needed for highly specialized use-cases requiring unique algorithms or configurations.
  • Data Privacy
    Storing and processing sensitive data on an external service may raise concerns regarding data privacy and compliance with data protection regulations.
  • Learning Curve
    Despite its ease of use, there is still a learning curve associated with mastering the AWS ecosystem and effectively utilizing its machine learning capabilities.

Grapple features and specs

  • Automatic Data Refresh
    Hourly data refresh from your favorite apps like Salesforce, Hubspot, Zendesk, Stripe, and more!
  • Universal Data Library
    Automatic data modeling ensures your data is clean and queryable
  • Natural Language
    Filter, visualize, and calculate with just your words—no SQL required.
  • Map Data
    Combine, merge, and map data from across disparate sources for a full picture of your business.
  • AI Data Scientist
    Create custom calculations and aggregations across multiple sources without writing any SQL or formulas
  • Unlimited Sharing
    Share with your team, view-only users are completely free
  • Dashboard Templates
    Build new dashboards from curated templates so you're never starting from scratch

Analysis of Amazon Machine Learning

Overall verdict

  • Amazon Machine Learning is a good fit for businesses that need a reliable cloud-based machine learning platform, especially those already utilizing AWS services. Its scalability and integration capabilities make it suitable for a wide range of machine learning tasks.

Why this product is good

  • Amazon Machine Learning offers scalable solutions integrated with AWS services, making it a strong choice for users already within the AWS ecosystem. Its tools are built to handle large datasets and provide robust infrastructure, contributing to ease of deployment and management. Additionally, the service enables developers and data scientists to build sophisticated models without requiring deep machine learning expertise.

Recommended for

  • Developers and data scientists seeking seamless integration with AWS cloud services.
  • Organizations handling large-scale data analyses and machine learning projects.
  • Enterprises that prioritize scalability and flexibility in their machine learning operations.
  • Teams looking for a platform that supports both novice and expert users with varying levels of machine learning expertise.

Analysis of Grapple

Overall verdict

  • Grapple (askgrapple.com) can be a solid choice for teams and individuals seeking an AI-powered tool to streamline their workflows, though its suitability depends on your specific needs and budget. As with any SaaS product, it's best to verify current features and pricing directly and take advantage of any free trial before committing.

Why this product is good

  • Offers AI-driven automation that can help save time on repetitive tasks
  • Designed with an intuitive interface aimed at reducing the learning curve
  • Can integrate into existing workflows to boost overall productivity
  • Typically provides responsive customer support and onboarding resources
  • May offer flexible pricing tiers to suit different team sizes

Recommended for

  • Small to medium-sized businesses looking to automate routine processes
  • Teams seeking to improve collaboration and productivity
  • Individuals or startups exploring AI tools on a budget
  • Users who value ease of use and quick setup over complex configurations

Amazon Machine Learning videos

Introduction to Amazon Machine Learning - Predictive Analytics on AWS

More videos:

  • Tutorial - AWS Machine Learning Tutorial | Amazon Machine Learning | AWS Training | Edureka

Grapple videos

Ask Grapple: DIY Data Platform

More videos:

  • Review - Watch this Before Buying a Grapple
  • Review - Don't Waste Your Money! Episode 1. Land Pride Grapple.
  • Review - Tractor Grapple Review

Category Popularity

0-100% (relative to Amazon Machine Learning and Grapple)
AI
100 100%
0% 0
Data Analytics
0 0%
100% 100
Developer Tools
100 100%
0% 0
Business Intelligence
0 0%
100% 100

Questions & Answers

As answered by people managing Amazon Machine Learning and Grapple.

Why should a person choose your product over its competitors?

Grapple's answer:

Grapple is built for small to medium-sized companies who haven't successfully implemented traditional BI software like Looker, Power BI, Tableau, or other solutions like DataRails and Domo. Traditional BI software requires a lot of technical knowledge to setup, maintain, and they often make it really difficult for less technical users to customize. This means your dashboards either 1) don't work, or 2) aren't flexible and easy to use enough to let operators adjust them as they need during the course of businesses.

Grapple is designed from the beginning for non-technical operators across marketing, sales, and finance.

How would you describe the primary audience of your product?

Grapple's answer:

Grapple is great for data savvy operators who love working with data. We're particularly helpful for companies with 25 to 500 employees who serve other businesses (B2B) and are focused on improving their CRM analytics and SaaS metrics. If you're using apps like Salesforce, Hubspot, Zendesk, Stripe, or Asana, Grapple is for you!

If you want to write data notebooks in python or SQL and want under-the-hood control of your data stack, Grapple is not for you. We recommend you try Omni or Hex.

What's the story behind your product?

Grapple's answer:

Jack, co-founder/CEO, had the idea for Grapple a couple years ago after spending almost a decade building in Tableau, Looker, Google Data Studio, Trevor.io, and the list goes on! Jack spent a lot of time collaborating with non-technical users in sales, marketing, bizops, finance on dashboards and after one particularly simple report that was still difficult to generate, he thought there must be a better way! Turns out, most data platforms require a ton of other tools and a ton of other people all of which are slow and expensive—delaying your time-to-insight. Jack had the idea to compress the data stack into a single tool, that maybe couldn't do everything, but would be the fastest, easiest way to pull the types of reports he pulled all the time over the last 10 years. Fast-forward to today, Andrew joined as co-founder/CTO and Grapple is now generally available and includes a suite of AI features to take Grapple's speed and ease of use even further. Let us know what you think!

What makes your product unique?

Grapple's answer:

Grapple is a fully vertically integrated data platform and does not require any additional tooling. Unlike competitors Looker and PowerBI, Grapple includes everything you need to get started. Frustrated by your slow data team? Get started with Grapple right away.

In nerd speak, Grapple seamlessly bundles the following tools, you won't even need to manage them: - An ETL and data warehouse for centralizing your data - Automatic data modeling so your data is queryable right away - Visualization and analytics UI

And on top of all that, Grapple provides modern functionality too: - Unlimited Viewers: share your dashboards with as many users as you want, just like a Google Docs - AI/Natural Language: customize your dashboard with natural language instead of SQL or spreadsheet formulas - Straightforward pricing: pay as you go with monthly per user pricing

Which are the primary technologies used for building your product?

Grapple's answer:

Grapple's application layer is written in React + Laravel and under the hood uses a mixture of PostgreSQL and No-SQL to deliver data warehousing and analytics capabilities.

User comments

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Social recommendations and mentions

Based on our record, Amazon Machine Learning seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Amazon Machine Learning mentions (2)

  • Rant + Planning to learn full stack development
    There’s also the ML as a service (MLaaS) movement that lowers the barrier for common ML capabilities (eg image object detection and audio transcription). Basically, you use APIs. See: https://aws.amazon.com/machine-learning/. Source: about 4 years ago
  • Ask the Experts: AWS Data Science and ML Experts - Mar 9th @ 8AM ET / 1PM GMT!
    Do you have questions about Data Science and ML on AWS - https://aws.amazon.com/machine-learning/. Source: over 5 years ago

Grapple mentions (0)

We have not tracked any mentions of Grapple yet. Tracking of Grapple recommendations started around Jun 2025.

What are some alternatives?

When comparing Amazon Machine Learning and Grapple, you can also consider the following products

Apple Machine Learning Journal - A blog written by Apple engineers

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

Machine Learning Playground - Breathtaking visuals for learning ML techniques.

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

Lobe - Visual tool for building custom deep learning models

Microsoft Power BI - BI visualization and reporting for desktop, web or mobile