object storage

  • Object storage, also known as object-based storage, is a flat structure in which files are broken into pieces and spread out among hardware. In object storage, the data is broken into discrete units called objects and is kept in a single repository, instead of being kept as files in folders or as blocks on servers.
  • Data, identifier and metadata
  • Object storage volumes work as modular units: each is a self-contained repository that owns the data, a unique identifier that allows the object to be found over a distributed system, and the metadata that describes the data. That metadata is important and includes details like age, privacies/securities, and access contingencies.
  • pros 
    it enables the storage of massive amounts of unstructured data while still maintaining easy data accessibility.
infinite scalability
  • cons: 
    Objects can’t be modified—you have to write the object completely at once.
  • use cases
    1. unstructured data like multimedia files
    2. large data sets

file storage

  • File storage, also called file-level or file-based storage, is exactly what you think it might be: Data is stored as a single piece of information inside a folder
  • To access a file, users or machines only need the path from directory to subdirectory to folder to file.
  • pros
    1. easy to share
    2. fast to navigate
  • cons
    1. not easy to expand storage, limitation on hierachy and permissions
  • use cases
    1. store files for directory
    2. Storage of data that requires data protection and easy deployment

block storage

  • data is broken up into pieces called blocks, and then stored across a system that can be physically distributed to maximize efficiency. Each block receives a unique identifier, which allows the storage system to put the blocks back together when the data they contain are needed.
  • when data is requested, the underlying storage software reassembles the blocks of data from these environments and presents them back to the user.
  • pros
    1. quickly retrieve and manipulate data
    2. decouple data
  • cons
    1. expensive
    2. limited capability to handle metadata, need rely on application or database level
  • use cases
    1. storage of databases
    2. cricital system data

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