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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
Gartner Recommended Reading
Critical Capabilities Methodology
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