Software Alternatives, Accelerators & Startups

Algorithmia VS Dataiku

Compare Algorithmia VS Dataiku and see what are their differences

Algorithmia logo Algorithmia

Algorithmia makes applications smarter, by building a community around algorithm development, where state of the art algorithms are always live and accessible to anyone.

Dataiku logo Dataiku

Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.
  • Algorithmia Landing page
    Landing page //
    2023-09-14
  • Dataiku Landing page
    Landing page //
    2023-08-17

Algorithmia

Pricing URL
-
$ Details
Release Date
2014 January
Startup details
Country
United States
State
Washington
City
Seattle
Founder(s)
Diego Oppenheimer
Employees
10 - 19

Dataiku

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

Algorithmia videos

How To Color Black and White Photos Automatically: Algorithmia Review

More videos:

  • Tutorial - How to Colorize Black and White photos online - Algorithmia Review (TopTen AI)
  • Review - Algorithmia | Getting started: Pipelines and MLOps

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

Category Popularity

0-100% (relative to Algorithmia and Dataiku)
Data Science And Machine Learning
Data Science Notebooks
100 100%
0% 0
Data Science Tools
0 0%
100% 100
Machine Learning Tools
100 100%
0% 0

User comments

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Reviews

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

Algorithmia Reviews

We have no reviews of Algorithmia yet.
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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....

Social recommendations and mentions

Based on our record, Algorithmia seems to be more popular. It has been mentiond 5 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.

Algorithmia mentions (5)

Dataiku mentions (0)

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

What are some alternatives?

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

Managed MLflow - Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete Machine Learning lifecycle with enterprise reliability, security, and scale.

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

neptune.ai - Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.

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

MCenter - Machine Learning Operationalization

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