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Actian Blog / Introducing Actian VectorH 6

Introducing Actian VectorH 6

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Actian VectorH 6 Enables User Defined Functions, Machine Learning, Semi-Structured Data Support, and Enhancement of Workload Management Capabilities.

Actian is pleased to announce the availability of Actian VectorH 6.  This release includes new features, including User Defined Functions (UDFs), JSON Support, and Workload Management.

This post provides an overview of some features that have been added to this release.

Key New Features

User-Defined Functions

User-defined functions (UDFs) let the user extend the database to perform operations that are not available through the built-in, system-defined functions provided by Vector. VectorH 6 provides the capability to create Scalar UDFs, which return at most one row, consisting of a single column/value. This means that you can run JavaScript of Python code alongside your SQL statement in a single query.

Vector supports three programming languages for UDFs: SQL, JavaScript, and Python 3.6 (in beta). An additional use case for UDFs in Vector is for the deployment of machine learning (ML) models that run alongside the database. By deploying machine learning models alongside the Vector database, data movement is reduced, thus allowing for faster scoring of data.

For example, Regex pattern matching that is not available in Vector today can be implemented with a UDF. In addition, some functions such as simple lookup tables can be completed with a join, but are far easier to create in a JavaScript UDF.

Workload Management

Workload management in database management systems (DBMSs) is the method of monitoring and managing work (i.e., database transactions) executing within a database system. Through control of work in a database, this allows the efficient use of system resources and the ability to maintain performance objectives. In VectorH 6, Actian has started to lay the groundwork for comprehensive workload management within the Vector database by enabling the control of the database access mode, limiting the row count returned by a given query, and the ability to abort queries should they reach pre-defined limits.

JSON Support

JSON (JavaScript Object Notation) is a popular semi-structured data format that is used for exchanging data in web and mobile applications. JSON is a flexible, easy to read, and a lightweight method for sharing data between applications.

JSON functions in Vector enable you to combine NoSQL and relational concepts in the same database. Now you can combine classic relational columns with columns that contain documents formatted as JSON text in the same table and parse and import JSON documents in relational structures. Vector 6  provides functionality to work with JSON objects directly in the database. Bridging semi-structured data with relational databases creates a solution that is more flexible, and can handle additional use cases where the underlying data structures change more rapidly. Some examples include; working with REST APIs and working with data in Business Intelligence (BI) and Data Science tools where the structure changes.

Additional Enhancements

This latest Vector release continues to develop its performance capabilities. These performance capabilities have been further refined in VectorH 6. In addition, new encryption capabilities and stability fixes are incorporated in the latest version.

Platform Support

Actian VectorH 6 continues to support RHEL, CentOS, SUSE Linux, Ubuntu, Cloudera, and Hortonworks. VectorH 6 is available today from esd.actian.com. Vector 6 for Linux will be available in Q2 2020, and Windows in Q3 2020.

About Adam Luciano

Adam Luciano is currently Director of Product Management at Actian Corporation. Adam is responsible for management of analytics products inclusive of Avalanche, Vector, and DataFlow as well as AI/ML technologies. Adam previously worked at Liberty Mutual Insurance where he built a home grown Data Science Platform. Previous to Liberty Mutual, Adam worked in digital marketing analytics, product management / product marketing in healthcare technology, market research, and investment analytics on Wall Street.