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DataBloom AI VS Habitify

Compare DataBloom AI VS Habitify and see what are their differences

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DataBloom AI logo DataBloom AI

Empowering Data, Elevating Decisions: Blossom Sky.

Habitify logo Habitify

The easiest way to keep track of your habits
  • DataBloom AI Landing page
    Landing page //
    2023-08-14

DataBloom AI is a leading contributor to Apache Wayang, developing "Blossom Sky," an AI-focused virtual data lakehouse platform that enables federated data access on the edge in order to train AI models directly at the source, uniquely combining the advantages of data lakes with data meshes.

  • Habitify Landing page
    Landing page //
    2023-07-14

DataBloom AI

Website
blossomsky.io
Pricing URL
Official DataBloom AI Pricing
$ Details
freemium €89.0 / Monthly (10 Users)
Platforms
Cross Platform Cloud AWS Azure GCP Alibaba IBM Cloud
Release Date
2022 February
Edit details

Habitify

Website
habitify.me
Pricing URL
-
$ Details
-
Platforms
iPhone Mac OSX Android Apple Watch
Release Date
-
Edit details

DataBloom AI features and specs

  • Data Access: Yes
  • Federated Data Processing: Yes
  • Data Regulation Management: Yes
  • Freemium: Yes
  • Open Source: Yes

Habitify features and specs

No features have been listed yet.

DataBloom AI videos

+ Add

Revolutionizing Financial Data Flow: Blossom Sky's Solution to Data Silos.

More videos:

  • Review - What is the Blossom Sky Virtual Data Lakehouse?

Habitify videos

+ Add

Habitify for iOS | 2019 Review - Features, Opinions & Pricing

More videos:

  • Review - YOU NEED THIS TO BE SUCCESSFUL! - Habitify App Review!
  • Review - Habitify launches Web edition

Category Popularity

0-100% (relative to DataBloom AI and Habitify)

DataBloom AI

Habitify

Developer Tools
100 100%
Developer Tools
0% 0
Productivity
0 0%
Productivity
100% 100
Data Integration
100 100%
Data Integration
0% 0
Habit Building
0 0%
Habit Building
100% 100

User comments

Share your experience with using DataBloom AI and Habitify. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, DataBloom AI seems to be more popular. It has been mentiond 3 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.

DataBloom AI mentions (3)

  • Python interface in beta
    Databloom.ai has released a dev environment: https://github.com/databloom-ai/BDE/blob/main/readme.md. Source: about 2 years ago
  • The Missing Piece in ML-based Query Optimization
    Blogpost via databloom.ai: Https://engineering.databloom.ai/2022/03/the-missing-piece-in-ml-based-query.html. Source: about 2 years ago
  • Challenges and opportunities towards AI solutions adoption
    Artificial intelligence solutions have been revolutionizing the industry continuously in the last decades. The benefits delivered by these technologies are numerous and diverse; among others you can find: capacity to improve work efficiency, capacity to analyze big datasets, automate infrastructure for easy escalation, enhance customer experience, etc. Nowadays companies are challenging themselves to obtain... Source: about 2 years ago

Habitify mentions (0)

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

What are some alternatives?

When comparing DataBloom AI and Habitify, you can also consider the following products

Xata - The data platform for modern web applications

Habit List - Create good habits and break bad ones with the app that keeps you focused.

Leanbe.ai - Data-driven smart roadmap generation platform

Momentum - Agile goal and performance management

Statwing - Simply upload your spreadsheet or dataset, then select the relationships you want to explore. Statwing was built by and for analysts, so you can clean data, explore relationships, and create charts in minutes instead of hours.

everyday.app - Every day, it gets a little easier. But you gotta do it every day, that's the hard part.

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