Published: 15 December 2022
Summary
Data and analytics leaders looking for analytic data management solutions will find a good range of choices to meet their needs. The market for cloud-based DBMSs for analytical use cases has matured and settled in the past year, with a mix of modernized traditional and newer offerings.
Included in Full Research
Overview
Key Findings
Vendors now embrace the cloud. In previous years, different vendor offerings did not fully embrace cloud attributes, instead using “cloudwashing” to appear to have cloud-based products. This is no longer the case. Vendors with decades of experience on-premises now offer fully cloud-based services.
Vendors are moving toward richer data ecosystems.Many solution areas that relate to database management, such as data quality, data governance, master data management and data integration, are becoming more tightly integrated with (and within) cloud analytics platforms. This richer functionality is being offered through new product capabilities and partners.
Mature vendors are getting more ‘cloudy’ while cloud-native
Clients can log in to view the entire
document.
Strategic Planning Assumptions
- Alibaba Cloud (Alibaba AnalyticDB)
- Amazon Web Services (Amazon Redshift)
- Cloudera (Cloudera CDP)
- Couchbase (Couchbase Capella)
- Databricks (Databricks Lakehouse Platform)
- Google (Google BigQuery)
- IBM (IBM Db2 Warehouse)
- InterSystems (InterSystems IRIS)
- MarkLogic (MarkLogic Data Hub)
- Microsoft (Azure Synapse Analytics)
- Neo4j (Aura: Graph Data Platform)
- Oracle (Autonomous Data Warehouse)
- SAP (SAP Data Warehouse Cloud)
- Snowflake (Snowflake Data Cloud)
- Tencent Cloud (TBDS)
- Teradata (Teradata Vantage)
- TigerGraph (TigerGraph Cloud)
- Analytics
- Analytics on Streaming Data
- Stream Optimization
- Operational Intelligence
- Data Science
- Multicloud/Intercloud/Hybrid
- Distributed Capabilities
- Financial Governance
- Application Development Support
- Performance Features
- Relational Attributes
- Multimodel Support
- Management and Administration
- Resource Usage
- Traditional Data Warehouse
- Logical Data Warehouse
- Data Lake
- Streaming Analytics
Gartner Recommended Reading
Critical Capabilities Methodology