New technologies for analyzing biological samples, like next generation sequencing, are producing a growing amount of data together with quality scores. Moreover, software tools (e.g., for mapping sequence reads), calculating transcription factor binding probabilities, estimating epigenetic modification enriched regions or determining single nucleotide polymorphism increase this amount of position-specific DNA-related data even further. Hence, requesting data becomes challenging and expensive and is often implemented using specialised hardware. In addition, picking specific data as fast as possible becomes increasingly important in many fields of science. The general problem of handling big data sets was addressed by developing specialized databases like HBase, HyperTable or Cassandra. However, these database solutions require also specialized or distributed hardware leading to expensive investments. To the best of our knowledge, there is no database capable of (i) storing billions of position-specific DNA-related records, (ii) performing fast and resource saving requests, and (iii) running on a single standard computer hardware.