Microsoft SQL Server Features

Collects, stores, and organizes massive, unstructured data in real time

Facilitates the disseminating of collected big data throughout parallel computing clusters

Creates a repository to collect and store raw data from sensors, devices, machines, files, etc.

Aligns processing and distribution workflows on top of Apache Hadoop

Aligns processing and distribution workflows on top of Apache Hadoop

Facilitates solution to run on and scale to a large number of machines and systems

Curates collected data for big data analytics solutions to analyze, manipulate, and model

Aligns processing and distribution workflows on top of Apache Hadoop

Moves big data collection and processing to the cloud

Processes batch, real-time, and streaming data workloads in singular, multi-tenant, or cloud systems

Allows data movement from one database to another.

Provides data backup and recovery functionality to protect and restore a database.

Allows users to access and work on data concurrently, supporting several views of the data.

Data is backed up automatically to prevent data loss

Transformation of data from one format to another

Stores the database metadata, that is the definitions of data elements, types, relationships etc.

Creates a copy of the database to maintain consistency and integrity.

Allows users to create, update and retrieve data in a database.

Defines the logical design of the data before building the schemas.

Monitors and analyzes critical database attributes like query performance, user sessions, dead lock detail, system errors etc and visualize them on a custom dashboard.

Synchronizing data between two or more devices/systems and automatically updating changes to maintain consistency

Receive data and information in real time

Manage and store data in a database

Encrypts and transforms data at the database from a readable state into a ciphertext of unreadable characters.

Allows restricted user acess to modify depending on the access level.

Access software remotely via mobile devices

Prevents other users and applications from accessing data while it is being updated to avoid data loss or update.

Allows permissions to be granted or revoked in the database, schema or table levels.

Built-in native encryption with enterprise key management.

Provides multi-factor authentication with certificates.

Provides support for international character sets and full text search.

Supports multiple data types like primitive, structured, document etc.

Supports multiple procedural programming languages like PL/PGSQL, Perl, Python etc.

Available on multiple operating systems like Linux, Windows, MacOS etc.

Provides data recovery functionality to protect and restore data in a database.

Allows multi-version concurrency control.

Handles workloads, from single machines to data warehouses or web services with many concurrent users.

Allows users to quickly retrieve data through various types of indexing like B-tree, hash table etc.

Helps interpret SQL queries and determine the fastest method of execution.

Data is organized as a set of tables with columns and rows like a table structure.

Allows users to create, update and retrieve data in a database.

Adheres to ACID (atomicity, consistency, isolation, durability), a set of database transaction properties.

Provides log-based or/and trigger-based replication.

Create, design and manage workflows for repetitive tasks

Set up connections to third-party platforms to improve business processes

Automatically retrieve and pull information from documents, websites, images, data sets, and other sources

Database management based on relationships between data

Security protocol that ensures secure, encrypted communication over the internet, safeguarding sensitive data from unauthorized access

Application programming interface that allows for integration with other systems/databases

Connect to big data sources

Search and filter data across systems to locate required information by entering keywords or certain criteria

Collection, analysis, and representation of numerical data and generation of reports to understand various patterns

Pre-designed layouts that can be customized to match preferences and requirements

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Search for specific words or phrases within a document or database

Retrieve and use data without requiring technical details about the data

Import and export data to and from software applications

Use AI to generate content in the form of text, images, videos, etc.

Assemble applications and processes by dragging over and arranging pre-built components

Customize data fields to support various needs and use cases

Verify the identity of users/devices to enable secure access

Graphical representation of data

Securely stores data to prevent data loss or breaches

Dashboard to view the status of ongoing processes, identify current incidents and track past activities

Track the management and flow of data throughout the organization

Run stored procedures and queries in multiple programming languages, such as JSON, Java, Python, Ruby, Perl, and SQL

Import, collect, and capture data from multiple sources

Manage user accounts, profiles, roles, permissions, and other details across applications, devices or networks

Database management based on customization, fluidity, and document relations

Define levels of authorization for access to specific files or systems

Track and manage schedules and meetings via an integrated calendar

Active monitoring of systems, applications, or networks

Store and organize documents in a centralized system

Plan, schedule, and execute organization's accounts and assets to ensure compliance with policies and laws

Manage patient documentation describing all clinical interactions, diagnoses, procedures, medications, etc.