Critical Capabilities for Data Management Solutions for Analytics

Archived Published: 16 March 2017 ID: G00314186

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Data management solutions for analytics are evolving rapidly, with new deployment scenarios, data sources and analytics requirements driving the market. Data and analytics leaders can use this research to guide evaluation and buying criteria for modern DMSA offerings.

Table of Contents

  • What You Need to Know
  • Analysis
    • Critical Capabilities Use-Case Graphics
    • Vendors
      • 1010data (Insights Platform)
      • Amazon Web Services (Amazon Redshift)
      • Cloudera (Cloudera Enterprise)
      • EnterpriseDB (EDB Postgres)
      • Google (BigQuery)
      • Hewlett Packard Enterprise (HPE Vertica)
      • Hortonworks (HDP)
      • Huawei (FusionInsight)
      • IBM (DB2)
      • MapR Technologies (Converged Data Platform)
      • MarkLogic
      • MemSQL
      • Microsoft (SQL Server)
      • MongoDB
      • Oracle
      • Pivotal (Greenplum)
      • SAP (SAP Hana)
      • Snowflake Computing
      • Teradata
      • Transwarp Technology (TDH)
    • Context
    • Product/Service Class Definition
    • Critical Capabilities Definition
      • Managing Large Volumes of Data
      • Loading Data Continuously
      • Query Optimization
      • Queries Support Analytics
      • Queries to Multiple Data Sources
      • Operational BI Use
      • System Availability
      • Administration and Management
      • Traditional Data Warehouse Use
      • Discovery Use
    • Use Cases
      • Traditional Data Warehouse
      • Operational Data Warehouse
      • Logical Data Warehouse
      • Context-Independent Data Warehouse
    • Vendors Added and Dropped
      • Added
      • Dropped
  • Inclusion Criteria
    • Critical Capabilities Rating
  • Gartner Recommended Reading
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