The article explores the architectural foundations of data organization in high-performance NoSQL database management systems, particularly document-oriented ones. It examines the data structure at all levels—from bits and blocks to pages, documents, and collections—forming a unified model of data control. Document-based databases (MongoDB, RavenDB, LiteDB) are shown to provide flexibility, scalability, and high performance through semi-structured storage formats (JSON, BSON), schema-free design, and CRUD operation support. The paper analyzes how data organization, indexing, caching, denormalization, and sharding affect system efficiency. Special attention is paid to index structures such as B-Tree and B-Tree+, transactional mechanisms aligned with ACID principles, and the application of the CAP theorem in distributed environments. A comparative analysis of MongoDB, RavenDB, and LiteDB architectures is presented regarding transaction processing, indexing, scalability, and query handling. The study concludes that a well-designed data organization architecture in NoSQL systems is a key factor ensuring flexibility, performance, reliability, and resilie
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