Published: 25 July 2018
Summary
This Hype Cycle helps data and analytics leaders interested in data management strategies to understand the evolutionary pace of maturing and emerging data management technologies. There is a noticeable lack of new technologies entering the Hype Cycle, while many are approaching the plateau.
Included in Full Research
- What You Need to Know
- The Hype Cycle
- The Priority Matrix
- Off the Hype Cycle
- On the Rise
- DataOps
- Private Cloud dbPaaS
- At the Peak
- Machine Learning-Enabled Data Management
- Data Classification
- File Analysis
- Time Series DBMS
- Data as a Service
- Data Catalog
- SQL Interfaces to Cloud Object Stores
- Event Stream Processing
- In-Process HTAP
- Blockchain
- Multimodel DBMSs
- Sliding Into the Trough
- Data Preparation
- Distributed Ledgers
- Point-of-Decision HTAP
- Data Lakes
- Graph DBMSs
- Spark
- Information Stewardship Applications
- Metadata Management Solutions
- Cross-Platform Structured Data Archiving
- Application Data Management
- Key-Value DBMSs
- Master Data Management
- Wide-Column DBMSs
- Operational In-Memory DBMS
- Hadoop SQL Interfaces
- iPaaS for Data Integration
- In-DBMS Analytics
- Logical Data Warehouse
- Climbing the Slope
- Document Store DBMSs
- SaaS Archiving of Messaging Data
- Data Integration Tools
- Enterprise Information Archiving
- Analytical In-Memory DBMS
- Content Migration
- Entering the Plateau
- Database Encryption
- Data Virtualization
- In-Memory Data Grids
- Database Platform as a Service
- Appendixes
- Hype Cycle Phases, Benefit Ratings and Maturity Levels