Gartner Research

Critical Capabilities for Cloud Database Management Systems for Analytical Use Cases

Summary

As the move to cloud continues apace, data and analytics leaders can now choose from a wide variety of cloud-based DBMSs for analytical use cases. This research, one of two Critical Capabilities reports providing context for the Magic Quadrant for Cloud DBMS, will help in their evaluation.

Published: 24 November 2020

ID: G00468198

Analyst(s): Henry Cook ,  Donald Feinberg ,  Merv Adrian ,  Rick Greenwald ,  Adam Ronthal

Table Of Contents

Overview

Strategic Planning Assumptions

What You Need to Know

Analysis

  • Alibaba Cloud (Apsara AnalyticDB for PostgreSQL)
  • Amazon Web Services (Amazon Redshift)
  • Cloudera (CDP)
  • Databricks (UDAP)
  • Google (BigQuery)
  • Huawei (GaussDB (DWS))
  • IBM (Db2 Warehouse Cloud)
  • InterSystems (IRIS)
  • MarkLogic (Data Hub Service)
  • Microsoft (Azure Synapse Analytics)
  • Oracle (ADW)
  • Redis Labs (Enterprise Cloud)
  • SAP (Data Warehouse Cloud)
  • Snowflake (Cloud Data Platform)
  • Tencent (Big Data Suite)
  • Teradata (Vantage)
  • Advanced Analytics
  • Automated Distributed Data Scaling
  • Automated Perf Tuning/Optimization
  • Consistency
  • Dynamic Elasticity (Scalable Perf)
  • Financial Governance
  • High-Speed, High-Volume Processing
  • High-Speed Ingest
  • Multi/Intercloud/Hybrid Deployment
  • Multiple Data Types/Structures
  • Performance Monitoring and Admin
  • Security
  • Workload Management
  • Data Warehouse
  • Logical Data Warehouse
  • Data Science/Deep Learning
  • Operational Intelligence

Inclusion Criteria

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Critical Capabilities Methodology

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