SplitByte offers both a desktop client and a web application for organizations to identify and split their data using the specifications (m, n, and the stream cipher). Splitting occurs right at the edge, providing complete security when splits are being transmitted over the network bandwidth. The data can be retrieved by the same user or another user with designated access and permission. Retrieval also occurs right at the client.
If during retrieval, the threshold quorum of shares are not accessed in a a specified time frame, SplitByte alerts the client of a suspicious activity.
The application will also provide daily logs for each split share location.
SplitByte complements and layers on top of AES as an additional layer of defense. It’s keyless approach to security, along with inherent redundancy and fault tolerance avoid any single point of failure.
The splits can be stored on either NAS locations, local hard drives, AWS, S3, Azure, Google or other public cloud platforms. Servers can be hosted or owned by the client, SplitByte or a third party company.
All unstructured and semi-structured data can be protected using SplitByte. This includes data types such as PDF, DOC, DOCX, XLS, picture formats, audio files, video files and beyond.
SplitByte supports all file systems such as SAN, NAS, and Azure Storage. Integrations with Google Drive, Sharepoint, MS Teams, Slack and Box are currently being developed and will be available soon.
The current product supports a Windows desktop client and a web based application which can be accessed via URL.
SplitByte’s added protection and security comes with a small storage overhead. Because the data is read from multiple splits, retrieval is actually faster as it would be with a traditional RAID array.
SplitByte integrates with the different data sources using REST API calls to pull data in for processing while maintaining the integrity of the data at source. SplitByte also offers an option to delete data at the source at the time of ingestion.
Even though data is split into several pieces, the storage overhead is not equivalent to the number of pieces. Total overhead differs from case to case, and depends on the total number of splits as well as the threshold retrieval number.
SplitByte is designed to store petabytes of data without losing any data integrity while seamlessly integrating with various data sources and cloud providers.