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.
Gartner defines a data science and machine learning platform as an integrated set of code-based libraries and low-code tooling that support the independent use by, and collaboration between, data scientists and their business and IT counterparts through all stages of the data science life cycle. These stages include business understanding, data access and preparation, experimentation and model creation, and sharing of insights. They also support machine learning engineering workflows including creation of data, feature, deployment and testing pipelines. The platforms are provided via desktop client or browser with supporting compute instances and/or as a fully managed cloud offering. Data science and machine learning (DSML) platforms are designed to allow a broad range of users to develop and apply a comprehensive set of predictive and prescriptive analytical techniques. Leveraging data from distributed sources, cutting-edge user experience, and native machine learning and generative AI (GenAI) capabilities, these platforms help to augment and automate decision making across an enterprise. They provide a range of proprietary and open-source tools to enable data scientists and domain experts to find patterns in data that can be used to forecast financial metrics, understand customer behavior, predict supply and demand, and many other use cases. Models can be built on all types of data, including tabular, images, video and text for applications that require computer vision or natural language processing.
Gartner defines intelligent document processing (IDP) solutions as specialized data integration tools enabling automated extraction of data from multiple formats and varying layouts of document content. IDP solutions ingest data for dependent applications and workflows, and can be provided as a software product and/or as a service. Organizations receive and process documents in multiple formats to enable activities such as onboarding new suppliers, receiving applications for loans or insurance claims. This results in large numbers of documents, the content of which is designed for people to comprehend rather than machines to process. Extracting data from content is essential for document processing and the automated activities this supports. IDP solutions fulfill this role, augmented by and potentially replacing people.