The big data challenge in bioinformatics is approaching. Data storage and processing, instead of experimental technologies, are becoming the slower and more costly part of research. Biological data typically have large size and a variety of structures. The ability to efficiently store and retrieve the data is important in bioinformatics research. Traditionally, large datasets are either stored as disk-based flat-files or in relational databases. These systems become more complicated to plan, maintain and adjust to big data applications as they follow rigid table schema and often lack scalability, e.g. for data aggregation. Meanwhile, non-relational databases (NoSQL) emerge to provide alternative, flexible and more scalable data stores.