Gartner Research

Critical Capabilities for Cloud Database Management Systems for Analytical Use Cases


The move to cloud continues apace. Data and analytics leaders can now choose from a wide variety of cloud-based DBMS for analytical use cases. This research will help in the evaluation of the strengths and weaknesses of both native services offered by CSPs and fully cloud-based systems.

Published: 14 December 2021

ID: G00740717

Analyst(s): Rick Greenwald Merv Adrian Adam Ronthal Philip Russom Henry Cook

Table Of Contents


Strategic Planning Assumptions

What You Need to Know


  • Alibaba Cloud (AnalyticDB for PostgreSQL)
  • Amazon Web Services (Amazon Redshift)
  • Cloudera (Cloudera Data Platform)
  • Couchbase (Couchbase)
  • Databricks (Lakehouse Platform)
  • Exasol (Exasol)
  • Google (Google BigQuery)
  • IBM (IBM Db2 Warehouse on Cloud)
  • InterSystems (InterSystems IRIS)
  • MariaDB (SkySQL)
  • MarkLogic (MarkLogic Data Hub Service)
  • Microsoft (Azure Synapse Analytics)
  • Oracle (Autonomous Data Warehouse)
  • SAP (SAP Data Warehouse Cloud)
  • SingleStore (SingleStore Managed Service)
  • Snowflake (Data Cloud)
  • Teradata (Vantage)
  • Advanced Analytics
  • Automated Perf Tuning/Optimization
  • Distributed Access
  • Dynamic Elasticity
  • Financial Governance
  • High-Speed Processing and Ingest
  • Multi/Intercloud/Hybrid Deployment
  • Performance Monitoring and Admin
  • Workload Management
  • Data Warehouse
  • Logical Data Warehouse
  • Data Lake
  • Operational Intelligence

Inclusion Criteria

Gartner Recommended Reading

Critical Capabilities Methodology

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