Software Alternatives, Accelerators & Startups

IBM Analytics Engine VS data.world

Compare IBM Analytics Engine VS data.world and see what are their differences

This page does not exist

IBM Analytics Engine logo IBM Analytics Engine

Analytics Engine is a combined Apache Spark and Apache Hadoop service for creating analytics applications.

data.world logo data.world

The social network for data people
  • IBM Analytics Engine Landing page
    Landing page //
    2023-07-11
  • data.world Landing page
    Landing page //
    2023-09-26

data.world

Website
data.world
Release Date
2015 January
Startup details
Country
United States
State
Texas
City
Austin
Founder(s)
Brett Hurt
Employees
50 - 99

IBM Analytics Engine features and specs

  • Scalability
    IBM Analytics Engine allows you to scale resources up or down based on demand, which helps optimize performance and costs.
  • Integration with IBM Cloud
    It integrates seamlessly with other IBM Cloud services, providing enhanced capabilities for data processing and analytics within the cloud ecosystem.
  • Support for Multiple Analytics Engines
    The platform supports various analytics engines like Apache Spark and Apache Hadoop, giving users flexibility in choosing tools that best fit their analytics needs.
  • Automated Management
    IBM Analytics Engine offers automated cluster management and maintenance, which reduces the operational burden on IT teams.
  • Cost Efficiency
    Pay-as-you-go pricing model allows businesses to manage costs effectively by only paying for the resources they use.

Possible disadvantages of IBM Analytics Engine

  • Complexity
    The learning curve can be steep for users unfamiliar with cloud-based analytics tools or the specific engines supported by the platform.
  • Dependency on Internet Connectivity
    As a cloud-based service, consistent and reliable internet connectivity is required for optimal performance and accessibility.
  • Limited Offline Capabilities
    The service primarily operates in the cloud with limited offline capabilities, which might not be suitable for environments where offline access is crucial.
  • Potential for Vendor Lock-In
    Migrating away from IBM Analytics Engine to another platform might require significant effort and resources, raising concerns about vendor lock-in.
  • Data Privacy Concerns
    Storing and processing data in the cloud can raise data privacy and compliance concerns, especially for businesses in regulated industries.

data.world features and specs

  • Collaborative Environment
    data.world provides a platform for teams to collaborate on data projects in real-time, making it easier for data scientists, analysts, and enthusiasts to work together and share insights.
  • Integration Capabilities
    The platform supports integrations with popular tools and services like Excel, Tableau, and Python, making it easier to import, export, and manipulate data across various applications.
  • Extensive Dataset Catalog
    data.world offers a vast collection of public datasets, empowering users to find and leverage data from a wide range of sources for their projects.
  • Querying Tools
    Users can execute SQL queries directly on the data.world platform, enabling powerful data analysis and transformations within the environment.
  • User-Friendly Interface
    The platform features an intuitive user interface that makes it accessible for users with varying levels of technical expertise.

Possible disadvantages of data.world

  • Pricing
    While data.world offers a free tier, more advanced features and functionality require a paid subscription, which might be cost-prohibitive for individuals or smaller organizations.
  • Learning Curve
    Despite its user-friendly interface, there is still a learning curve associated with fully utilizing all of the platform's features, particularly for users who are not familiar with SQL or data analysis tools.
  • Performance Limitations
    For very large datasets or complex analytical operations, the platform may experience performance constraints, potentially requiring users to rely on more powerful, external data processing tools.
  • Data Privacy Concerns
    As with any cloud-based platform, there are inherent data privacy and security concerns. Users must be cautious about the sensitivity of the data they upload and ensure compliance with relevant regulations.
  • Feature Parity with Competitors
    While data.world offers many great features, some users might find that other data collaboration platforms provide more advanced or specialized tools that better suit their needs.

Analysis of data.world

Overall verdict

  • Overall, data.world is regarded as a beneficial platform for data enthusiasts, professionals, and organizations looking to collaborate on data projects. Its user-friendly interface, strong community focus, and extensive features make it a valuable resource for those working with data.

Why this product is good

  • data.world is considered a good platform for a variety of reasons. It acts as a collaborative data community where users can discover and share open data. The platform provides tools for collaborative data projects, making it easier for users to work together on data analysis and insights. It also supports a wide range of data formats and offers integrations with other tools and platforms, enhancing its versatility. Additionally, data.world emphasizes openness and transparency, which can foster trust among users who are seeking reliable data sources.

Recommended for

  • Data analysts and scientists who need a collaborative environment to work on data projects.
  • Organizations looking to share and manage their data with a broader community.
  • Educators and researchers seeking open data sets for teaching or scholarly purposes.
  • Business professionals who require integration with other data tools for enhanced data insights.

Category Popularity

0-100% (relative to IBM Analytics Engine and data.world)
Data Dashboard
18 18%
82% 82
Big Data
100 100%
0% 0
Data Integration
0 0%
100% 100
Data Management
100 100%
0% 0

User comments

Share your experience with using IBM Analytics Engine and data.world. For example, how are they different and which one is better?
Log in or Post with

Social recommendations and mentions

Based on our record, data.world seems to be more popular. It has been mentiond 24 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.

IBM Analytics Engine mentions (0)

We have not tracked any mentions of IBM Analytics Engine yet. Tracking of IBM Analytics Engine recommendations started around Mar 2021.

data.world mentions (24)

  • Is data at every company still an absolute mess?
    I'll be sure to check out data.world propose to use it if it makes sense, thanks. Source: over 2 years ago
  • GIS data for a project. I apologize for the banality of my request and for my English.
    Just google qgis datasets. There are so so many interesting sets you will find. Check out qgis.org, or data.world for starters. Source: over 2 years ago
  • Best way to open source a my dataset?
    But, I'm also aware that there are dedicated platforms to catalog and share data (e.g. https://www.dolthub.com/, https://data.world/), and that uploading data on Github, in general, doesn't seem best practise. Source: over 2 years ago
  • Alation vs. Atlan vs. Collibra
    The client is considering the 3 I mentioned, plus data.world. I need to research that one next. Microsoft Purview has already been considered. Source: over 2 years ago
  • Looking for christmas cost dataset by year and country.
    Im looking for Christmas cost dataset by year and country, Im looking in the data.world and other web pages and I cant found anything. Source: almost 3 years ago
View more

What are some alternatives?

When comparing IBM Analytics Engine and data.world, you can also consider the following products

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Denodo - Denodo delivers on-demand real-time data access to many sources as integrated data services with high performance using intelligent real-time query optimization, caching, in-memory and hybrid strategies.

Snowflake - Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.

IBM Cloud Pak for Data - Move to cloud faster with IBM Cloud Paks running on Red Hat OpenShift โ€“ fully integrated, open, containerized and secure solutions certified by IBM.

Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

K2View Fabric - K2View Fabric provides a data-centric approach to data management that delivers access to key data in real-time through patented mico-databases.