Gartner defines the market for cloud database management systems (DBMSs) as the market for software products that store and manipulate data and that are primarily delivered as software as a service (SaaS) in the cloud. Cloud DBMSs may optionally be capable of running on-premises, or in hybrid, multicloud or intercloud configurations. They can be used for transactional and/or analytical work. They may have features that enable them to participate in a wider data ecosystem. They typically persist data using proprietary components in a durable manner, enabling a full range of create, read, update and delete operations.
Reviews for 'Customer Relationship Management - Others'
Gartner defines a data science and machine learning platform as an integrated set of code-based libraries and low-code tooling. These platforms support the independent use and collaboration among data scientists and their business and IT counterparts, with automation and AI assistance through all stages of the data science life cycle, including business understanding, data access and preparation, model creation and sharing of insights. They also support engineering workflows, including the creation of data, feature, deployment and testing pipelines. The platforms are provided via desktop client or browser with supporting compute instances or as a fully managed cloud offering.
Reviews for 'Data and Analytics - Others'
Gartner defines the market for data and analytics (D&A) services as consulting and system integration (C&SI) and managed services. These services manage data for all uses (operational and analytical), and analyze data to drive business processes and improve business outcomes through more effective decision making. The core capabilities for vendor solutions in the D&A services market include: D&A strategy and operating model design Data management Analytics and business intelligence (ABI) Data science and machine learning D&A governance Program management Enterprise metadata