Software Alternatives & Startups

Dataiku VS Amplication

Compare Dataiku VS Amplication and see what are their differences

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.

Dataiku logo Dataiku

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

Amplication logo Amplication

Instantly generate Node.js apps with GraphQL and REST API
  • Dataiku Landing page
    Landing page //
    2023-08-17
  • Amplication Landing page
    Landing page //
    2023-09-10

Dataiku

$ Details
-
Release Date
2013 January
Startup details
Country
United States
State
New York
City
New York
Founder(s)
Clément Stenac
Employees
500 - 999

Dataiku features and specs

  • 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 of Dataiku

  • 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.

Amplication features and specs

  • Rapid development
    Amplication allows developers to quickly generate and modify backend applications, reducing development time significantly.
  • Open-source
    Being open-source, Amplication provides transparency and allows developers to contribute to the project, ensuring continuous improvement and community support.
  • Scalability
    Amplication's architecture is designed to be scalable, making it suitable for both small projects and large, complex applications.
  • Customizability
    Developers can easily customize the generated code to fit specific business requirements, providing flexibility in application development.
  • Integration capabilities
    Amplication supports integration with various databases and third-party services, enhancing the functionality of the generated applications.
  • User-friendly interface
    The platform boasts an intuitive interface that simplifies the application creation process even for developers with minimal experience.

Possible disadvantages of Amplication

  • Early-stage product
    As a relatively new product, Amplication might not have all the features and refinements of more mature backend development tools.
  • Learning curve
    Despite its user-friendly interface, there may still be a learning curve for developers unfamiliar with the concepts of automated backend generation.
  • Limited ecosystem
    Compared to longstanding platforms, Amplication has a smaller ecosystem of plugins, templates, and community resources.
  • Dependency on specific technologies
    Amplication may limit developers to specific technologies and frameworks, which could be a downside for projects requiring unconventional tech stacks.
  • Potential for over-reliance on automation
    Heavy reliance on automated tools like Amplication may lead to less understanding of underlying backend processes among developers.
  • Performance optimization
    Automatically generated code may require additional performance tuning and optimization compared to hand-crafted solutions.

Analysis of Amplication

Overall verdict

  • Amplication is generally considered a good choice for developers looking for an easy-to-use platform that speeds up the development process without sacrificing flexibility or customization.

Why this product is good

  • Amplication is a powerful open-source development tool that simplifies the process of building back-end applications. It provides a user-friendly interface, accelerates development with automated code generation, and integrates seamlessly with various tech stacks. Developers appreciate its customization options and robust documentation, which help reduce the complexity and time required for back-end development.

Recommended for

  • Developers who want to quickly prototype and build back-end applications
  • Teams looking for a collaborative and open-source development tool
  • Projects that need scalable and maintainable back-end solutions
  • Users who want a tool that integrates easily with existing technologies

Dataiku videos

AutoML with Dataiku: And End-to-End Demo

More videos:

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

Amplication videos

Bullet AC -100 CR Acoustic Guitar Amplication review by www.Guitarthai.com

Category Popularity

0-100% (relative to Dataiku and Amplication)
Data Science And Machine Learning
APIs
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Developer Tools
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Dataiku and Amplication

Dataiku Reviews

15 data science tools to consider using in 2021
Some platforms are also available in free open source or community editions -- examples include Dataiku and H2O. Knime combines an open source analytics platform with a commercial Knime Server software package that supports team-based collaboration and workflow automation, deployment and management.
The 16 Best Data Science and Machine Learning Platforms for 2021
Description: Dataiku offers an advanced analytics solution that allows organizations to create their own data tools. The company’s flagship product features a team-based user interface for both data analysts and data scientists. Dataiku’s unified framework for development and deployment provides immediate access to all the features needed to design data tools from scratch....

Amplication Reviews

We have no reviews of Amplication yet.
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Social recommendations and mentions

Based on our record, Amplication seems to be more popular. It has been mentiond 71 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.

Dataiku mentions (0)

We have not tracked any mentions of Dataiku yet. Tracking of Dataiku recommendations started around Mar 2021.

Amplication mentions (71)

  • Top 15 Open-Source Low-Code Projects with the Most GitHub Stars
    GitHub Https://github.com/amplication/amplication GitHub Stars 14.8k Most Recent Update on GitHub Within one day Open Source License Apache 2.0 Number of Active Contributors This Year 15 Acceptance of External PRs Yes Official Website Https://amplication.com/ Documentation Https://docs.amplication.com/. - Source: dev.to / about 2 years ago
  • Extending GitOps: Effortless continuous integration and deployment on Kubernetes
    The application used in this demonstration was generated through Amplication, which allows you to generate production-ready backend services - reliably, securely, and consistently. - Source: dev.to / over 2 years ago
  • Auth0 and Amplication: Simplifying Authentication in Your Applications
    Setting up Auth0 authentication in your Amplication application is easy. You can use the Auth0 plugin to add the required dependencies and configuration files to your application. The steps are as follows:. - Source: dev.to / almost 3 years ago
  • Node.js Worker Threads Vs. Child Processes: Which one should you use?
    Additionally, you can use tools like Amplication to bootstrap your Node.js applications easily and focus on these parallel processing techniques instead of wasting time on (re)building all the boilerplate code for your Node.js services. - Source: dev.to / almost 3 years ago
  • Top 6 ORMs for Modern Node.js App Development
    In addition, Prisma is supported by microservice code generation tools like Amplication. Prisma plugs directly into the code generated by Amplication. By doing so, you can utilize Prisma as an ORM layer for your databases and generate microservice code with ease in just a few clicks. - Source: dev.to / almost 3 years ago
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What are some alternatives?

When comparing Dataiku and Amplication, you can also consider the following products

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

KeystoneJS - Open source framework for developing database-driven websites, applications and APIs in Node.js.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Hasura - Hasura is an open platform to build scalable app backends, offering a built-in database, search, user-management and more.

NumPy - NumPy is the fundamental package for scientific computing with Python

Sheet 2 Site - Generate a website from 📗 Google Sheets