- Data are chopped up into blocks of bytes, leaving the system unknown as to what is stored until all the blocks are put back together.
- Data are able to be retrieved at low latency. Very high performance. However, this means that storage cannot have a lot of distance between each other, generally multiple servers will be in the same physical location from each other.
- Cannot deal with many users editing the same file. No locking ability among data.
- No metadata. Very little over head.
- NAS index tables have a max size, limited to the amount of data to be indexed or stored due to performance hit. Therefore, scalability is limited.
- Requires backup to an offsite location for redundancy.
- Stores data in a file hierarchy or known as directories and sub-directories. Similar to how linux/UNIX systems organize their files.
- Has a set uncustomizable metadata for each file, things like file name, creation date, file type etc...
- Allows many users to edit the same data. Has locking features, however, is handled by the operating system and not by the file system itself.
- Designed to be on a local network or remote network. Flexible on location, however, impacting latency further the servers are. Performance is not a concern.
- NAS index tables have a max size, limited to the amount of data to be indexed or stored due to performance hit. Therefore, scalability is limited.
- Requires backup to an offsite location for redundancy.
- Stores data in objects, each object has an unique ID, metadata and the actually data itself. Each object is then stored into buckets or a group of objects, the user can decide which bucket each object can be placed in.
- Meant to organize unstructured data, whether that is videos, music, documents, or pictures into a flat organization with flexibe sized buckets.
- Limited to the number of users allowed the edit the same file at a time. If many users do edit the same file, object storage will instead create different versions of that object.
- Buckets can be stored in multiple nodes and geographic locations. This creates builtin redundancy and improves performance.
- Allows custom metadata, this allows the filtering or processing in finding the correct data by storing custom data pertaining to each object. For example, YouTube would use a category type in this metadata to find cat videos versus dog videos.
- Since Object Storage uses a GUID for each object, we can scale the number of objects easily instead of relying on NAS which uses complex file paths to determine where data are.