How it Works
RainStor employs sophisticated data and pattern de-duplication techniques to achieve typically 40x data compression when compared to traditional databases. This remarkable level of compression significantly reduces storage footprints and enables highly efficient scalability on commodity hardware.
Unique pattern de-duplication technology
The de-duplication techniques used within RainStor do not result in any loss of detail – data is not summarized or aggregated in RainStor. Instead RainStor stores each record as a series of pointers to the location of a single instance of a data value, or pattern of data values. RainStor uses a tree-based structure to store data that links the various instances of the patterns together to establish data records. This means that the original data records can be reconstituted at any time. This de-duplication process also means that the greater the amount of data, the higher the probability that patterns will be repeated, and the greater the level of compression that can be achieved when the data is loaded. The greater the amount of data loaded, the more efficient RainStor becomes.
To learn more about the data and pattern de-duplication techniques employed by RainStor, read the post describing our secret sauce in the RainStor blog.
Design-free data store
The creation of the RainStor data repository is a very simple process – the data definition language (DDL) of the source data is supplied to RainStor, which is used to automatically build the structure of the repository without any database design. When data is imported into RainStor, the data is automatically de-duplicated and compressed. Applying changes to the structure or schema of the repository is equally simple – the DDL changes are supplied to RainStor and they’re automatically applied to the schema of the repository. In addition, RainStor keeps a record of all the schema changes through a versioning mechanism that allows the repository to be rolled back to any point in time.
Index-free query performance
The fast response times of queries gives the impression that RainStor uses indexes that must be maintained and optimized. However, RainStor uses sophisticated algorithms to “learn” the patterns in the data and store them as single instances. When RainStor receives a query, it parses and processes the query to identify the subset of patterns that contain the query result. The query is then run over this reduced set of data, realizing huge benefits in performance.
Learn more about Rainstor in the cloud.