SQL Server 2017 brings the performance and security of SQL Server to Linux and Docker containers. SQL Server 2017 delivers mission critical OLTP database capabilities and enterprise data warehousing with in-memory technology across workloads.
Customers will gain trans-formative insights from in-database machine learning with Python and R, plus rich interactive reporting on any device for faster decision making. Developers can choose their language and platform while container support seamlessly facilitates DevOps scenarios.
Brand | Microsoft SQL Server Standard 2017 Core |
Product Type | Open License Product |
Version | 2016 |
Distribution Media | VLSC Portal Media |
System Requirements | 1.4Ghz 64-bit processor, RAM: 1 GB, Disk Space: 6 GB |
Feature 01 | The premium offering, SQL Server Enterprise edition delivers comprehensive high-end datacenter capabilities with blazing-fast performance, unlimited virtualization, and end-to-end business intelligence — enabling high service levels for mission-critical workloads and end user access to data insights. |
Feature 02 | End-to-end database security with Always Encrypted. |
Feature 03 | Enhanced in-memory performance for all workloads. |
Feature 04 | Basic reporting. |
Feature 05 | Basic analytics. |
Feature 06 | Hybrid scenarios: Stretch Database, backup. |
Feature 07 | SQL Server Database Engine includes the Database Engine, the core service for storing, processing, and securing data, replication, full-text search, tools for managing relational and XML data, in database analytics integration, and Polybase integration for access to Hadoop and other heterogeneous data sources, and the Data Quality Services (DQS) server. |
Feature 08 | Analysis Services includes the tools for creating and managing online analytical processing (OLAP) and data mining applications. |
Feature 09 | Machine Learning Services (In-Database) supports distributed, scalable machine learning solutions using enterprise data sources. In SQL Server 2016, the R language was supported. SQL Server 2017 supports R and Python. |
Customers will gain trans-formative insights from in-database machine learning with Python and R, plus rich interactive reporting on any device for faster decision making. Developers can choose their language and platform while container support seamlessly facilitates DevOps scenarios.