The Air Force Test Center (AFTC) is engaged in the acquisition and analysis of aeronautical telemetry data from flight testsspecifically, HDF5 and IRIG data.Currently, these datatypes are isolated from one another.HDF5 data may be stored in an HDF Server, which provides remote access to large amounts of HDF5 data using a RESTful API.IRIG data, on the other hand, currently lacks a similar system to streamline the ingestion, manipulation, and analysis of the data.This lack of modern server technology for IRIG data combined with the lack of a mechanism to interrelate data results in several challenges in the discovery and analysis of the underlying data:We propose a high performance distributed data server solution named CHIMERA that addresses multiple problems inherent in dealing with large datasets.It addresses data format complexity up front, allowing the system to leverage mainstream proven Big Data technologies for scalability and performance.It then builds upon this by overlaying advanced data analytics techniques to provide users with far more control and insight into the underlying data.CHIMERA segregates data discovery from data querying, data analysis, and data processing.HDF5,IRIG,Telemetry Data,metadata extraction,Graph Database,Big Data,Hadoop,Spark