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.. even including your system files.
7.  One of the biggest issues with large, publicly-released data sets are the fact that the records are often compressed and that the headers on some of the files are mis-formatted. Therefore, the header information is not always read correctly by some of the tools. We also found that a number of the 'big data' tools had problems handling URLs.
9.  The majority of 'big data' tools are designed for use with Linux. However, many of the 'big data' tools have a Windows version available. There are many other tools and services available. For more information about those other tools, refer to the papers mentioned in [Table 6](#pone.0198210.t006){ref-type="table"}.
10. 'Big data' tools can perform just as well as, or even better than, the commonly used tools. However, many of the current tools are designed for reading and writing files in a specific format. For example, some of the tools we tested were only able to write files with a particular file format. For more information about the limitations of each tool, refer to the papers mentioned in [Table 7](#pone.0198210.t007){ref-type="table"}.
11. The 'big data' tools we tested were only able to handle files that were in a specific format. For example, the tools we tested were only able to read files with a particular format. For more information about the limitations of each tool, refer to the papers mentioned in [Table 8](#pone.0198210.t008){ref-type="table"}.
12. In general, all of the 'big data' tools we tested were able to do both reads and writes to and from files. However, there are a number of cases when one tool is able to do a one job better than another. For more information about the performance of each tool, refer to the papers mentioned in [Table 9](#pone.0198210.t009){ref-type="table"}.
10.1371/journal.pone.0198210.t006
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