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
- Search and query CSV, JSON, and Parquet format datasets located on external S3-compatible object storage platforms
- Write data stored on Vantage to external S3-compatible object storage platforms
- Amazon S3
- Google Cloud Storage
- Microsoft Azure Blob storage
- Microsoft Azure Data Lake Storage Gen2
See Teradata Vantage™ - Native Object Store Getting Started Guide and the Orange Book, Native Object Store: Teradata Vantage™ Advanced SQL Engine, TDN0009800. Both are located at https://docs.teradata.com/ (to see the Orange Book, you must Sign In).
In-Database Analytics
- Advanced SQL Engine Analytic Functions
-
Advanced SQL Engine can run path and patterning, time series, and model scoring functions for a variety of analytic models. The in-database analytics combined with the data management capability, results in high performance and quick decision making.
See Teradata Vantage™ - Advanced SQL Engine Analytic Functions.
- Vantage Analytics Library
-
Vantage Analytics Library provides the Data Scientist with over fifty advanced analytic functions built directly in the Advanced SQL Engine. These functions support the entire data science process, including exploratory data analysis, data preparation and feature engineering, hypothesis testing, as well as statistical and machine learning model building and scoring.
See Vantage Analytics Library User Guide.