The manufacturing industry is capitalizing on the data fabric applications to improve in strategic and real-time decision-making. The manufacturing industry works on thin margins; the operating margin reflected by this industry shows huge deviation on the profits and losses made by the organizations existing in this industry and is dynamic in nature. Therefore, the manufacturing industry has to continuously adapt to and change itself according to the unpredictable and disruptive innovations occurring in the market. Manufacturing industries handle multiple sets of data that need to be continuously captured and analyzed to streamline business applications and optimize business resources. The industry handles data from multiple sources such as in-factory data, along with analog data, images, raw sensor data, and information churned out from applications inside the factory and other sources, which include enterprise resource planning systems, manufacturing execution systems, time and attendance logs, supplier information, and various process automation and control systems. The data fabric helps them integrate, store, and analyze their data, which they can use to control their manufacturing systems and increase productivity.

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EVALUATION CRITERIA

Below criteria are most commonly used for comparing Data Fabric Software tools.
  • Breadth and Depth of Product Offerings
    • Solutions Offered
    • Licenses
    • Services
      • Education & Training
      • Support & Maintenance
      • Managed Services
      • Consulting Services
      • Deployment & Integration Services
    • Integration
      • Apache Spark
      • Apache Kafka
      • Apache Hadoop
      • Apache Storm
      • Apache Ranger
      • Enterprise Data Warehouses (EDWs) / External Databases
      • NoSQL
      • Others
  • Product Features and Functionality
    • Self-service Capabilities
    • Features Offered
      • Metadata Management
      • Data Governance
      • Data Virtualization
      • In-Memory Data Access
      • Distributed Computing
      • Data Transformation
      • Data Discovery
      • Data Quality
      • Data Integration
      • Data Security
      • Data Lineage
      • Data Orchestration
      • Specify Others
    • Data Prrocessing Techniques
      • Real-Time Streaming Data Processing (Data-in-Motion)
      • Batch Data Processing
    • Data Coverage
      • Unstructured Data
      • Semi-Structured Data
      • Structured Data
  • Delivery
    • End Users
      • Data Scientists
      • Business Analysts
      • Application Developers
      • Consultants
      • Other End Users
    • Deployment Model
      • Hosted / On-Cloud
      • Hybrid
      • On-Premise
    • Delivery Mode for Client Location
      • Subscription / Licensing
    • Channel of Delivery
      • Directly
      • Through Partners / Third-Party Vendors / MSSPs
  • Support and Services
    • Level of Support
    • Customer Redressal Mechanism/Program
    • services
      • Technical Support
      • Customer Support
      • Sales Support
      • Others, please specify
    • Channel for Delivery of Support Services
      • Remote Support
      • On-Site Support
  • Business Applications
    • Use Cases
      • Security Management
      • Fraud Detection
      • Risk and Compliance Management
      • Customer Intelligence
      • Sales Management
      • Marketing Management
      • Supply Chain Management
      • Business Process Management
      • Workforce Management
      • Other Cases
    • Business Functions Catered
      • Sales
      • Marketing
      • Human Resources (HR)
      • Finance
      • Product Development
      • Operations/Production
      • Supply Chain
      • Customer Service

TOP VENDORS

    • Enterprise
    • 501 to 1,000
  • #

    Denodo Technologies offers Denodo platform, which supports data fabric deployments such as big data analytics, virtual big data marts, IoT data processing, and real-time analytics. Additionally, it provides a comprehensive support for the Hadoop ecosystem to support enterprises with a Data Lake strategy (such as Vizient and Logitech).

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    • Startup
    • Palo Alto, California, US
    • Founded: 1999
    • $11MN to $50MN
    • 51 to 100
  • #

    Global IDS offers enterprise information management software, data ecosystem transparency suite, data ecosystem privacy suite, data ecosystem governance suite, data ecosystem rationalization suite, and data governance suite to cater to the data fabric needs. It provides companies with the software tools they need to move from ungoverned to governed data, while laying the foundation for data-centric computing in Hadoop/cloud infrastructures.

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    • Enterprise
    • 501 to 1,000
  • #

    HPE offers software-defined storage that eliminates complexity and helps free the infrastructure from the limitations of the dedicated hardware. It is a software-defined data fabric for any workload. The softwaredefined storage building blocks comprise HPE StoreVirtual Storage, HPE Synergy, HPE Hyper Converged Systems, Network Function Virtualization, HPE ProLiant DL Gen9 rack servers, and HPE Helion OpenStack.

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    • Enterprise
    • Palo Alto, California, United States
    • Founded: 2015
    • 10,001 to 15,000
  • #

    IBM offers various data management services, which empower business verticals to connect distinct data management and storage resources and streamline data management. IBM InfoSphere Information Server Enterprise Edition is one of the services that help by providing end-to-end integration capabilities and qualitative data.

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    • Enterprise
    • 1 to 50
  • #

    Informatica offers Informatica Platform in the data fabric market. The focus of the company is on increasing the productivity of developers owing to the visual and metadata driven development environment. Subsequently, it enables the reuse of workflow pipelines to support other infrastructures.

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    • Enterprise
    • Redwood City, California, US
    • Founded: 1993
    • $1BN to $5BN
    • 1,001 to 5,000
  • #

    NetApp’s Data Fabric solution is created to deal with structured, semi-structured, and unstructured data. It helps in addressing IT issues, such as gaining data visibility, increasing operational agility, and streamlining data protection.

    • Enterprise
    • 501 to 1,000
  • #

    Oracle offers a data grid, namely, Coherence, which combines data virtualization, transparent and distributed EIS integration, uniform accessibility, and queryability to provide data fabric. It provides various features including real-time application processing using parallel query, analyses aggregation, and live event and parallel transaction processing.

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    • Enterprise
    • California, USA
    • Founded: 1977
    • $10BN to $50BN
    • 1,00,001 to 5,00,000
    • Enterprise
    • 501 to 1,000
    • Startup
    • 1 to 50
  • #

    Software AG provides Terracotta In-Memory Data Fabric software solution. It stores a large amount of data that can be retrieved by multiple users in a fraction of a second. This enables fast and real-time data access and management with low latency. Terracotta can search data from a central depository without consuming time and provides scalable in-memory data management.

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    • Enterprise
    • Hessen, Germany
    • Founded: 1969
    • 1,001 to 5,000
  • #

    Splunk offers enterprise machine data fabric, which facilitates insights from data to provide operational intelligence. It is enabled by the Splunk platform, which manages data collection and flows, understands where data sits and provides the analytics and visualizations to make sense of that data at any scale. The enterprise machine data fabric is a combination of the Splunk platform, solutions, and ecosystem. The Splunk platform enables the enterprise machine data fabric to be at the center of an enterprise data workflow.

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    • Enterprise
    • San Francisco, California, US
    • Founded: 2003
    • $500MN to $1BN
    • 1,001 to 5,000
  • #

    Syncsort offers DMX-h and Ironstream products in the data fabric market. Syncsort DMX-h is specifically designed to help achieve modern data strategy objectives with a single interface for accessing and integrating all enterprise data sources—batch and streaming—across Hadoop, Spark, Linux, UNIX, or Windows, on-premises or in the cloud.

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    • SME
    • New Jersey, US
    • Founded: 1968
    • $101MN to $500MN
    • 501 to 1,000
  • #

    Talend Data Fabric works as a platform and combines all integration products to resolve complex IT integration issues. This is a compatible platform for on-premises, cloud, and hybrid environments. It allows developers to use single integration tools in order to address various types of problems. With the use of Data Fabric platform, the company provides various products for big data integration, data integration, cloud integration, application integration, self-service data preparation, and master data management.

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    • SME
    • Redwood City, California, US
    • Founded: 2005
    • $51MN to $100MN
    • 501 to 1,000
  • #

    Teradata offers data fabric enabled by Teradata QueryGrid. The data fabric weaves together multiple analytics, diverse data repositories, and disparate systems to provide business users a cohesive and uninterrupted analytics ecosystem. Teradata QueryGrid orchestrates query execution across multipleprocessing engines and repositories in a secure and optimized manner. It minimizes data movement and data duplication and processes data where it resides. It enables easy bi-directional data movement.

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    • Enterprise
    • California, US
    • Founded: 1979
    • $1BN to $5BN
    • 10,001 to 15,000
    • SME
    • 1 to 50
  • #

    VMware creates solutions that enable digital transformation for its customers as they transform their applications, infrastructure, and devices for their future business needs. VMware offers vFabric Data Director and Pivotal GemFire. Pivotal GemFire is a distributed data management platform. Pivotal GemFire is designed for many diverse data management situations but is especially useful for high-volume, latencysensitive, mission-critical, transactional systems.

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    • Enterprise
    • 15,001 to 20,000

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