  Astrophysical research in recent decades has made significant progress thanks
to the availability of various $N$-body simulation techniques. With the rapid
development of high-performance computing technologies, modern simulations have
been able to take the computing power of massively parallel clusters with more
than $10^5$ GPU cores. While unprecedented accuracy and dynamical scales have
been achieved, the enormous amount of data being generated continuously poses
great challenges for the subsequent procedures of data analysis and archiving.
As an urgent response to these challenges, in this paper we propose an adaptive
storage scheme for simulation data, inspired by the block time step integration
scheme found in a number of direct $N$-body integrators available nowadays. The
proposed scheme, namely the block time step storage scheme, works by minimizing
the data redundancy with assignments of data with individual output frequencies
as required by the researcher. As demonstrated by benchmarks, the proposed
scheme is applicable to a wide variety of simulations. Despite the main focus
of developing a solution for direct $N$-body simulation data, the methodology
is transferable for grid-based or tree-based simulations where hierarchical
time stepping is used.
