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Dataiku VS Apache CXF

Compare Dataiku VS Apache CXF and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Dataiku logo Dataiku

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

Apache CXF logo Apache CXF

Apache CXF, Services Framework - Index
  • Dataiku Landing page
    Landing page //
    2023-08-17
  • Apache CXF Landing page
    Landing page //
    2019-12-29

Dataiku

Website
dataiku.com
Pricing URL
Official Dataiku Pricing
$ Details
-
Release Date
2013 January
Startup details
Country
United States
State
New York
City
New York
Founder(s)
Clément Stenac
Employees
500 - 999
Edit details

Apache CXF

Website
cxf.apache.org
Pricing URL
-
$ Details
Release Date
-
Edit details

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.

Apache CXF features and specs

  • Comprehensive Web Service Support
    Apache CXF supports a wide range of web service standards including SOAP, REST, and various WS-* standards, allowing developers to work with different service types under one framework.
  • Flexibility
    CXF is highly configurable and can be customized to meet various needs ranging from simple web APIs to complex enterprise integrations, supporting both XML and JSON formats.
  • Integration
    It integrates well with other Java enterprise standards and frameworks such as Spring and JAX-RS, offering seamless integration into existing systems.
  • Active Community and Documentation
    Being an Apache project, CXF benefits from a large, active community which contributes to extensive documentation, forums, and community support.
  • Performance
    Apache CXF is designed to be lightweight and efficient, which can lead to better performance in web service communication compared to some heavier alternatives.

Possible disadvantages of Apache CXF

  • Complexity for Beginners
    The extensive features and flexibility of Apache CXF can make it complex for beginners to get started, requiring a good understanding of web service concepts and configurations.
  • Steep Learning Curve
    Due to its wide range of capabilities and configurability, mastering Apache CXF may involve a steep learning curve for developers, especially those new to web services or enterprise integration.
  • Documentation Gaps
    While there is extensive documentation, it can sometimes be outdated or lacking in detailed examples for complex configurations and newer features, which can be challenging for developers needing specific information.
  • Overhead for Simple Use-Cases
    For very simple REST or SOAP web services, Apache CXF may introduce more complexity and overhead than necessary compared to more lightweight alternatives or simpler frameworks.

Dataiku videos

+ Add

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

Apache CXF videos

+ Add

15-Generating Code - SOAP WSDL to Java using Apache CXF Plugin | Maven for Beginners | Code Journal

Category Popularity

0-100% (relative to Dataiku and Apache CXF)

Dataiku

Apache CXF

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Ruby Web Framework
0 0%
Ruby Web Framework
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 Apache CXF

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.
Source: searchbusinessanalytics.techtarget.com
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....
Source: solutionsreview.com

Apache CXF Reviews

We have no reviews of Apache CXF yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Apache CXF 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.

Dataiku mentions (0)

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

Apache CXF mentions (2)

  • It's 2023. Your API should have a schema
    SOAP died because it is awful. There are plenty of java libraries that can generate java code from a WSDL. Apache CXF seem to be the fairly standard library people use. (https://cxf.apache.org). Source: about 3 years ago
  • What’s Coming in Jakarta REST 3.1?
    A few years back, Adam Bien wrote an excellent blog post on how to configure JSON-B in a Jakarta REST application. The only trouble is that at that time, the approach only worked with Eclipse Jersey. Since then other implementations (including Open Liberty via Apache CXF) also enabled this functionality, but it will become a standard in 3.1, enabling more portable usage of JSON-B configuration. - Source: dev.to / over 5 years ago

What are some alternatives?

When comparing Dataiku and Apache CXF, 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.

ASP.NET - ASP.NET is a free web framework for building great Web sites and Web applications using HTML, CSS and JavaScript.

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

jQuery UI - Curated set of user interface interactions, effects, widgets, and themes built on top of the jQuery JavaScript Library

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

Font Awesome - Font Awesome makes it easy to add vector icons and social logos to your website. And version 5 is redesigned and built from the ground up!

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