![]() In the past, this option was a tough call due to the lack of viable alternatives and lack of support, but this version has made it flawless. The relationship between the two allows entities to be linked together directly and can be retrieved in one operation. The significant concepts of graph databases are edges and nodes. Graph database components are a new addition to Microsoft SQL Server 2017. Some of the new string manipulation functions include: It has done away with the writing of lengthy T-SQL statements with temporary tables and complicated logic. This version of Microsoft SQL Server comes with an array of fantastic string manipulation functions. String functions handle string literals but in the process consume most of the query execution time in decoding the various parts of the character literals. You can always pick up from where you left. ![]() Consequently, you don’t have to rebuild an index that you had already built halfway. It allows you to resume, pause and even rebuild your indexes as you please. This version comes in handy to do away with such issues. As such, running such systems can be a hustle. While rebuilding indexes is quite a daunting engagement, most database management systems do not allow for offline maintenance. This server is the first of its type to support pause and resume functionality for index maintenance operations. This capability is based on Artificial Intelligence which tunes the database accordingly, checking and fixing issues. Such regular procedures include creation and maintenance of required indexes, dropping useless indexes and monitoring the system for optimum query performance. Microsoft SQL Server 2017 can help administrators to perform routine system check-out operations to identify and fix any problems. It sets itself apart from the other versions based on the following features: Automatic Database Tuning This version is a known platform that offers you a choice of development languages, data types, on-premises or cloud, and operating systems. This server ensures that all your data in the database is encrypted to prevent any unauthorized access. Transparent data encryption encrypts the data at rest.Row-level security and dynamic data masking you can track compliance for common organizational and regulatory standards with vulnerability check.You do not move your sensitive data outside the database since you can encrypt it with secure enclaves.Security measures have been put in place in this version to offer maximum security to your data. Compatibility certification you can upgrade and modernize your SQL Server on-premises and in the cloud with compatibility certification.Performance recommendations after system self-analysis.Built-in intelligence to monitor queries for flawless execution.Industry-Leading Performance and Availability Support UTF-8 characters for applications extending to a global scale.It can support custom Java code along the lines it executed R and Python.It can be deployed with multiple Linux distributions such as RedHat, SUSE, and Ubuntu.The server can run with Windows, Linux, and containers and has support for deployment on Kubernetes.In this niche, the following are now possible: As such, you can query data stored in Oracle, Teradata, HDFS or any other sources. This allows you to query data from a distinct focal point. Moreover, you can enhance your high-value data by combining it with big data and the ability to dynamically scale out compute to support analytics. You can now comfortably do analytics and AI over any data with power SQL and Apache Spark. Such include: Intelligence with SQL Server 2019 big data clusters It is superior to other versions and comes with equally superior features that place it at the top of the pyramid. This is the latest version of SQL Servers in the market today. Here is how each of the above versions of Microsoft SQL Server compares against each other in terms of features and other attributes. ![]() Each version comes with its defining attributes and serves different audiences and workloads. The first version was released back in 1989, and since then several other versions have broken into the market. It serves the purpose of data storing and retrieval as requested by other applications that are running in the same device or different computers over a network. Microsoft SQL Server is Microsoft's relational database management system.
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