Page 6
Data security, from on-premises to cloud, with encryption at rest and in motion as well as greater
compliance with row-level security
Even higher availability with AlwaysOn, including more replicas, load balancing, and automation
Enhanced database caching across multiple cores and enhanced Windows Server support
Mission-critical performance with SQL Server
SQL Server’s evolution mirrors the growing critical nature of data for enterprises. Data is the new
currency, and it has become a major competitive differentiator. Companies with a data-centric culture are
harnessing increasingly diverse data. This data is not just relational or internal, but includes both
relational and non-relational, as well as internal and external data sources. These companies are also
using new analytical models to not just look at historical data but to use historical data to predict the
future. Insights from the data are not limited to a few, but shared more broadly in the organization and
much of this analysis is at speed: near real-time in many cases. Companies with a data-centric culture are
more productive, more efficient with their operations, and innovate faster, leading to improvements in their
bottom line.
More than ever, organizations need mission-critical operations that are easy to deploy and are balanced
with faster time-to-solution. In this white paper, we review four main areas in which SQL Server continues
to deliver in this regard: performance, security, availability, and scalability. We conclude with information
about how to compare the total cost of ownership between SQL Server and other databases.
Performance
SQL Server consistently leads in performance benchmarks, such as TPC-E, TPC-H, and real-world
application performance. With SQL Server 2014 and the upcoming SQL Server 2016, performance is
enhanced with a number of new technologies, including in-memory, query store, JSON, and temporal
support, to name a few.
SQL Server’s integrated in-memory toolset goes far beyond isolated features and provides support for
improving performance dramatically in a wide range of scenarios. These technologies include in-memory
online transaction processing (OLTP), primarily for transactional workloads, and in-memory columnstore,
primarily for decision support workloads (this last one is discussed in the Deeper Insights white paper).
The new query store feature allows you to monitor query plans to optimize them for particular application
scenarios over time, providing additional performance-tuning opportunities. Native JSON support in the
core database engine is another new feature that provides support for working with schema-free data
within SQL Server. The new temporal database features allow you to record, audit, and query data
changes over time.
In-memory online transaction processing
In-memory technology for SQL Server dramatically improves the throughput and latency of SQL Server
OLTP capabilities. It is designed to meet the requirements of the most demanding transaction processing
applications, and Microsoft has worked closely with a number of companies to prove these gains.
剩余27页未读，继续阅读
dsstdsst
- 粉丝: 0
- 资源: 7
我的内容管理
展开
最新资源
- 构建Cadence PSpice仿真模型库教程
- VMware 10.0安装指南：步骤详解与网络、文件共享解决方案
- 中国互联网20周年必读：影响行业的100本经典书籍
- SQL Server 2000 Analysis Services的经典MDX查询示例
- VC6.0 MFC操作Excel教程：亲测Win7下的应用与保存技巧
- 使用Python NetworkX处理网络图
- 科技驱动：计算机控制技术的革新与应用
- MF-1型机器人硬件与robobasic编程详解
- ADC性能指标解析：超越位数、SNR和谐波
- 通用示波器改造为逻辑分析仪：0-1字符显示与电路设计
- C++实现TCP控制台客户端
- SOA架构下ESB在卷烟厂的信息整合与决策支持
- 三维人脸识别：技术进展与应用解析
- 单张人脸图像的眼镜边框自动去除方法
- C语言绘制图形：余弦曲线与正弦函数示例
- Matlab 文件操作入门：fopen、fclose、fprintf、fscanf 等函数使用详解
资源上传下载、课程学习等过程中有任何疑问或建议，欢迎提出宝贵意见哦~我们会及时处理！
点击此处反馈
