Top 10 reasons to choose SQL Server 2019
Transform your Business with a unified data platform, SQL Server 2019 comes with Apache Spark and Hadoop Distributed File System (HDFS) for intelligence over all your data. SQL Server 2019 brings innovative security and compliance features, industry-leading performance, mission-critical availability, and advanced analytics to all your data workloads, now with support for big data built-in.
SQL Server 2019 Features
SQL Server 2019 and Big Data
- Use big data clusters to bring high-value relational data and high-volume big data together on a single, scalable platform.
- Avoid slowdowns in extract-transform-load (ETL) processes with data virtualization—an alternative to ETL that integrates data from disparate sources, locations, and formats.
- Create data lakes and query data from many sources through a consistent interface.
- Add intelligent features and get better insights from your data analysis—including data stored beyond SQL Server in Hadoop, Oracle, Teradata, and MongoDB.
Why choose SQL Server 2019?
Harness the power of big data
Big data clusters with scalable compute and storage composed of SQL Server, Spark and HDFS. Cache data in scale-out data marts.
Bring AI to your workloads
A complete AI platform to train and operationalise models in SQL Server ML Services or Spark ML using Azure Data Studio notebooks.
Eliminate the need for data movement
Data virtualisation allows queries across relational and non-relational data without movement or replication.
Explore and interact with visual data
Visual data exploration and interactive analysis using SQL Server BI tools and Power BI Report Server.
Run real-time analytics on operational data
In memory technologies for analytics on operational data using HTAP. Higher concurrency and scale through persistent memory.
Automatically tune SQL Server
Intelligent Query Processing improves scaling of queries and Automatic Plan Correction resolves performance problems.
Reduce database maintenance and increase business uptime
Greater uptime with more online indexing operations. Now run Always On availability groups on containers using Kubernetes.
Boost security and protect data in use
SQL Server enables layers of security including protection of computations in Always Encrypted secure enclaves.
Track compliance with sophisticated resources
Data Discovery & Classification labelling for GDPR and Vulnerability Assessment tool to track compliance.
Optimise with choice and flexibility
Support for your choice of Windows, Linux and containers. Run Java code on SQL Server and store and analyse graph data.
How to download SQL Server 2019 ?
1. Go to SQL Server 2019 evaluation page.
2. Under Windows, click on the link Choose your installation setup.
3. On the next screen, click on Preview SQL Server 2019 for Windows link. This will open another web page for you.
4. Under SQL Server evaluations / SQL Server 2019 CTP / Start your evaluation, click on the Continue button.
5. Fill in the form in the next step and press the Continue button.
6. The download should start immediately. Do not close the page and if you lose the download link, just press the download button again and it will start downloading directly again so you don’t have to follow the above-mentioned steps again and again.
7. The above-downloaded file is a stub installer. You will need to run this file to download the actual ISO file in the language of your choice. To download the ISO file, run the installer and select Download Media box
8. On the next screen, select the language of your choice, ISO or CAB (compressed media for .exe and .box installation files.) and the location to save the downloaded file.
The SQL Server 2019 is available to download and evaluate on both Windows & Linux. Additionally, support for Containers & Kubernetes is added.
Summary
Microsoft is presenting SQL Server 2019 as a great application that comes with useful, advanced, and amazing utilities. SQL Server 2019 offers substantial enhancements that are going to improve the way we use relational database platform. Persistent memory support, clustering for Machine Learning Services, replication and distributed transactions on Linux, Kubernetes, connectors for Oracle / Teradata / MongoDB, synchronous AG replicas bump up to five Java support (implementation similar to Python/R) and the “Big Data Cluster.”
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