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Data-intensive systems are subject to continuous evolution that translates ever-changing business and technical requirements. System evolution usually constitutes a highly complex, expensive and risky process. This holds, in particular, when the evolution involves database schema changes, which in turn impact on data instances and application programs. This paper presents a comprehensive approach that supports the rapid development and the graceful evolution of data-intensive applications. The approach combines the automated derivation of a relational database from a conceptual schema, and the automated generation of a data manipulation API providing programs with a conceptual view of the relational database. The derivation of the database is achieved through a systematic transformation process, keeping track of the mapping between the successive versions of the schema. The generation of the conceptual API exploits the mapping between the conceptual and logical schemas. Database schema changes are propagated as conceptual API regeneration so that application programs are protected against changes that preserve the semantics of their view on the data. The paper describes the application of the approach to the development of an e-health system, built on a highly evolutive database.