Published: 24 November 2020
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.
Included in Full Research
Strategic Planning Assumptions
- 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
Gartner Recommended Reading
Critical Capabilities Methodology