Advanced SQL Engine (SQL Engine) includes embedded analytic functions supporting high-speed analytics processing required to operationalize analytics. It is the most comprehensive SQL Engine with the highest available and resilient data platform in the industry.
Advanced SQL Engine is designed for decision support. It handles complex data requirements and manages the data warehouse environment through the use of a parallel implementation that automatically distributes data and balances workloads. Parallel processing is an efficient method of handling complex tasks like ad-hoc queries, as it breaks a task into smaller subtasks that are managed concurrently by multiple work units. The support of query and workload parallelism in Advanced SQL Engine enables better performance and higher throughput levels as a relational database management system (RDBMS).
Native Object Store
Native Object Store (NOS) is a Vantage capability that enables Business Analysts, System Administrators, and Database Administrators to perform read-only searches and query CSV, JSON, and Parquet format datasets located on external object store using standard Teradata SQL and APIs.
- Amazon S3
- Microsoft Azure Blob storage
Highly Resilient Data Management
Advanced SQL Engine provides scalability by adding node interconnect capabilities through the Teradata BYNET®. Each processor node running the powerful BYNET software is connected to the dual high-speed Infiniband™. These interconnected nodes form a loosely-coupled, massively parallel processing (MPP) architecture that is managed as a single system. This approach provides the foundation for linear scalability in Teradata systems. A Teradata system is scalable to thousands of physical processors and tens of thousands of virtual processors (VProcs) from an initial single, two-processor node environment.
Advanced SQL Engine supports entry-level to massive enterprise data warehouse (EDW) solutions.
In-Database Analytics
Advanced SQL Engine has the ability to run path and patterning, time series, and model scoring functions for decision trees. The in-database analytics combined with the data management capability, results in high performance and quick decision making.