To achieve near-linear data scalability to exabytes and beyond, SAND’s MPP (Massively Parallel Processing) architecture uses decoupled shared storage in conjunction with full distributed processing, with dynamic allocation of resources to ensure consistent performance. SAND’s MPP architecture can be deployed in an Elastic Cloud, which expands and contracts according to real-time requirements.
SAND MPP is architected into every aspect of the SAND product. SAND Analytics data is stored in a shared location using the best available media, including tiered storage. SAND Analytics delivers concurrent data load and query capability in parallel, with parallel load streams enabling linear scalability.
MPP Extreme User Scalability
SAND Analytics delivers the most efficient Massively Parallel Processing architecture for large communities of users. SAND’s Workload Manager utilizes all resources available to process user requests, and features a virtual execution mode delivering non-locking, non-blocking file operations.
MPP Extreme Analytic Scalability
SAND Analytics is a column database delivering easy and powerful analytics. Query processing scans individual data fields instead of the entire record, eliminating the requirement to move unneeded fields in and out of memory. SAND’s approach greatly enhances performance for OLAP queries and pure ad hoc, advanced database analytics.
SAND tokenizes data for both storage and processing efficiency. Each row is augmented with a unique identifier, called a Tuple Identifier (TID), and in each column an Entity Identifier (EID) is assigned to each unique value. This dramatically improves performance and maintainability.
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