The paper considers the problem of providing auditing of granular transformations in heterogeneous Big Data processing systems. The use of distributed ledger technologies for tracking data fragment transformations is proposed. The authors make a comparison of technologies applicable to solve this problem, provide an analytical and experimental evaluation, recommendations for the application of the study results. In contrast to other similar works, the authors consider the application of various distributed ledger technologies and include the multiplatform requirement for the framework. The proposed framework is universal and can be used in heterogeneous multiplatform big data processing systems