Published: 14 December 2021
Summary
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.
Included in Full Research
Strategic Planning Assumptions
- Alibaba Cloud (AnalyticDB for PostgreSQL)
- Amazon Web Services (Amazon Redshift)
- Cloudera (Cloudera Data Platform)
- Couchbase (Couchbase)
- Databricks (Lakehouse Platform)
- Exasol (Exasol)
- Google (Google BigQuery)
- HUAWEI CLOUD (GaussDB(DWS))
- 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
Gartner Recommended Reading
Critical Capabilities Methodology