  The DEAP-3600 detector searches for dark matter interactions on a 3.3 tonne
liquid argon target. Over nearly a decade, from start of detector construction
through the end of the data analysis phase, well over 200 scientists will have
contributed to the project. The DEAP-3600 detector will amass in excess of 900
TB of data representing more than 10$^{10}$ particle interactions, a few of
which could be from dark matter. At the same time, metadata exceeding 80 GB
will be generated. This metadata is crucial for organizing and interpreting the
dark matter search data and contains both structured and unstructured
information.
  The scale of the data collected, the important role of metadata in
interpreting it, the number of people involved, and the long lifetime of the
project necessitate an industrialized approach to metadata management.
  We describe how the CouchDB and the PostgreSQL database systems were
integrated into the DEAP detector operation and analysis workflows. This
integration provides unified, distributed access to both structured
(PostgreSQL) and unstructured (CouchDB) metadata at runtime of the data
analysis software. It also supports operational and reporting requirements.
