Analytics Database 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.
Analytics Database 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 Analytics Database 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 available on Vantage as Parquet formatted datasets to S3-compatible object storage platforms
- Amazon S3
- Google Cloud Storage
- Microsoft Azure Blob storage
- Microsoft Azure Data Lake Storage Gen2
- Hitachi Content Platform
- MinIO
- Dell EMC ECS
- NetApp StorageGrid
- IBM Cloud Object Storage
- Scality Ring
See Teradata Vantage™ - Native Object Store Getting Started Guide and the Orange Book, Teradata Vantage™ Native Object Store Orange Book - 17.20. Both are located at https://docs.teradata.com/ (to see the Orange Book, you must Log In).
Highly Resilient Data Management
Analytics Database provides scalability by adding node interconnect capabilities through the Teradata BYNET®. Processor nodes running the powerful BYNET software 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.
Analytics Database supports entry-level to massive enterprise data warehouse (EDW) solutions.
In-Database Analytics
- Analytics Database Analytic Functions
- Analytics Database can run path and patterning, data preparation, model training, model scoring, and model evaluation 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™ - Analytics Database Analytic Functions.
- Vantage Analytics Library
- Vantage Analytics Library provides the Data Scientist with over fifty advanced analytic functions built directly in the Analytics Database. 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.
- Unbounded Array Framework
- Unbounded Array Framework (UAF) is a Teradata framework for building end-to-end time series forecasting pipelines. It also provides functions for digital signal pocessing and 4D spatial analytics. UAF provides data scientists with the tools for all phases of forecasting:
- Data preparation functions
- Data exploration functions
- Model coefficient estimation functions
- Model validation functions
- Model forecast functions
See Teradata Vantage™ - Unbounded Array Framework Time Series Reference