Application platforms provide runtime environments for application logic. They manage the life cycle of an application or application component, and ensure the availability, reliability, scalability, security and monitoring of application logic. They typically support distributed application deployments across multiple nodes. Some also support cloud-style operations (elasticity, multitenancy and self-service).
Data and Analytics refers to products and services that enable organizations to collect, integrate, analyze, and act on data to drive informed decision-making and business outcomes. This category includes markets that focus on empowering enterprises to manage data pipelines, ensure data quality and governance, extract insights through advanced analytics, and machine learning across structured and unstructured data environments.
A digital integration hub (DIH) is an architectural pattern that centralizes data from various sources to provide a scalable, and real-time layer for modern digital applications, especially beneficial for enterprises looking to transform to digitized sales processes. It aggregates data from multiple systems of record into a low-latency, high-performance data store (the data management layer) which is then accessed by sales force automation (SFA), sales enablement and other tools via APIs or events. It also provides a central layer of abstraction that decouples applications from underlying systems, making it easier to integrate and manage new data sources and applications without disrupting existing systems. DIH provides sales teams with rich and responsive access to massive data sources, limits the fees paid to API providers and helps enable 24/7 operations enhancing customer experience through self service, digital commerce and loyalty.
The market for ESP platforms consists of software subsystems that perform real-time computation on streaming event data. They execute calculations on unbounded input data continuously as it arrives, enabling immediate responses to current situations and/or storing results in files, object stores or other databases for later use. Examples of input data include clickstreams; copies of business transactions or database updates; social media posts; market data feeds; images; and sensor data from physical assets, such as mobile devices, machines and vehicles.