Here are some popular uses for object-oriented storage:
- Unstructured data, including music, video, images and multimedia files,
- Pharmaceutical and financial data,
- Backup, database dumps, and log files,
- Archived files, media resources,
- Historical data sets of a variety of nature; and,
- Sensor data.
Unlike relational databases with rows and columns, the object-oriented storage architecture stores data units in a structurally flat data environment. Each stored object includes metadata with descriptions and unique identifiers that store data linked between geographically dispersed nodes.
This storage system can scale infinitely by adding nodes. Because this approach allows you to set up automatic routing of data to the right storage systems. As a result, you discover objects even if they are not stored in the same physical location. Again, the object storage platform is designed to be “ultimately consistent.” This way, any application can find updated data in the entire object repository over time, which means finding the latest file without searching the file systems at your fingertips! Another great advantage of using this type of storage is that you can maximize disk size to scale up to several hundred petabytes of data stored in a single namespace. Currently, the added feature object storage solution is the most balanced architecture with which you can achieve storage scalability without sacrificing performance.
If you are a storage administrator responsible for scaling data to the petabyte range, you are sitting in the hot seat! Because you need to maximize your usable storage space. Indeed, you’re spoiled for choice with approaches like SAN and NAS systems, scalable file systems, or public cloud. But each approach has its own set of complexities, performance and data privacy issues. That’s where object storage comes in.
