Analytics query accelerators provide SQL or SQL-like query support on a broad range of data sources. They are most frequently used as a means of providing interactive and production-optimized delivery on semantically flexible data stores that do not inherently have the capabilities to provide sufficient performance or ease of use on their own. Commonly used in conjunction with data lakes, they aim to support BI dashboards, interactive query capabilities, data modeling and other analytics use cases.
The market for data integration tools consists of stand-alone software products that enable organizations to combine data from multiple sources and perform tasks related to data access, transformation, enrichment and delivery. They enable use cases such as data engineering, delivering modern data architectures, self-service data integration, operational data integration and supporting AI projects. Data management leaders procure data integration tools for their teams, including data engineers and data architects, or for other users, such as business analysts or data scientists. These products are primarily consumed as SaaS or deployed on-premises, in public or private cloud, or in hybrid configurations.
A lakehouse is a converged infrastructure design environment that combines the semantic flexibility of a data lake with the production optimization and delivery capabilities of a data warehouse. Data lakehouses are considered transformational and can serve as the foundational analytic data store for the organization. They are designed to unify the capabilities of data warehouses and data lakes into a single platform to support comprehensive data management and AI lifecycle.