Software Alternatives & Reviews

MarkLogic Data Hub Platform VS K2View Fabric

Compare MarkLogic Data Hub Platform VS K2View Fabric and see what are their differences

MarkLogic Data Hub Platform logo MarkLogic Data Hub Platform

Data Hub Central is the collaborative, self-service user experience for building your cloud data hub on MarkLogic Data Hub Service.

K2View Fabric logo 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.
  • MarkLogic Data Hub Platform Landing page
    Landing page //
    2023-08-20
  • K2View Fabric Landing page
    Landing page //
    2023-08-20

MarkLogic Data Hub Platform videos

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K2View Fabric videos

Intro to K2View Fabric

More videos:

  • Review - K2View Fabric Technical Overview: Data without delay, so you can be an IT superhero

Category Popularity

0-100% (relative to MarkLogic Data Hub Platform and K2View Fabric)
Data Dashboard
43 43%
57% 57
AI Platform
43 43%
57% 57
Data Integration
43 43%
57% 57
Data Management Platform (DMP)

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What are some alternatives?

When comparing MarkLogic Data Hub Platform and K2View Fabric, you can also consider the following products

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

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.

data.world - The social network for data people

Teradata QueryGrid - Data Fabric

Informatica Intelligent Data Platform - Unleash data's potential with Informatica infrastructure services that all roll up under a robust and intelligent data integration platform.

Cinchy - Developed for real-time data collaboration, Cinchy Dataware Platform addresses the root cause of data fragmentation and data silos, eliminates the cost and need for time-consuming data integration, and mitigates risks of data duplication.