Azure Data Factory Pricing & Demo

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Azure Data Factory
Redmond, USA
1975
Enterprise
78 Likes
65 Buyers Negotiating

Summary

Azure ETL software is a cloud integration system because of which data is moved on-premises and cloud systems as well as orchestrating and scheduling complex flows. The software focuses more on Extract-and-load as well as the Transform-and-Load platform rather than a traditional Extract-Transform-and-Load (ETL) platform. Azure ETL software is a robust software that is easy to learn, cost-efficient, scalable tool to improve business process agility and outcomes.

Azure Data Factory Pricing

The Azure Data Factory pricing plans are broadly stated in two categories that could be billed monthly or annually depending upon the plan that the user selected and the number of users who would use it. 

  1. Azure Data Factory pricing for Personal - ₹4199 per user per month
  2. Azure Data Factory pricing for Enterprise- ₹ 4736 per user per month

The Azure Data Factory pricing assesses, develops, and validates hand-on technical skills with an industry-leading training solution.

Azure Data Factory Demo

Azure Data Factory demo is basically a 7-day free trial to its customers with the liberty of canceling it anytime they wish to. This helps customers to get good hands over Azure ETL software till the time they are learning it.

Features

Data Configuration - Azure ETL software configures simple data flow and transfers data between file systems and database systems that are both on-premises and on the cloud. Connects to numerous database systems, like SQL Server, Oracle, Azure SQL Database, MySQL, DB2, as well as file storage and Big Data systems.

Job scheduling and orchestration - Azure ETL software allows building event-based data flows and dependencies, for instance, data flows can be configured to initiate when files are deposited into a certain folder. Aids data movement tasks and job scheduling out of other alternatives like SQL Agent services on SQL VM and Azure Scheduler.

Scalability - Azure ETL software handles huge data volumes using its built-in parallelism and time-slicing features. It helps to move a number of gigabytes of data into the cloud within a few hours.

Continuous integration and delivery - Develop, build, and automatically deploy due to integration with GitHub. Allows to create and deploy all the components using PowerShell if someone is skilled with PowerShell.

Minimal coding required - A unique interface named ADF v2 allows creating components from the Azure Portal interactively, with very little coding.

Discussions

Strengths
  • +8
    Auditing
  • +7
    Reporting
  • +8
    Consulting
  • +9
    System Integration
  • +12
    Automation
  • +9
    Extraction
  • +11
    Loading
  • +13
    Scalability
  • +10
    Transformation
  • +13
    Annual Subscription
  • +5
    Mobile App
  • +12
    Monthly Subsciption
  • +14
    Web-Based, Cloud, SaaS
  • +6
    Windows Installation
  • +10
    Customer Service
  • +12
    Data Quality Control
  • +13
    Match & Merge
  • +14
    Metadata Management
  • +5
    Non-Relational Transformations
  • +6
    Version Control
Cautions
  • -11
    Free
  • -7
    Mac Installation
  • -14
    One-Time Purchase

Azure Data Factory Reviews

user-icon

Buyer, Software, SME

5
May 02, 2020

“Reduce overhead costs”

This will preserve the ETL processes and reduce operational complexity with a fully managed experience when it is migrating SQL Server DB to the cloud.
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user-icon

Buyer, Construction, Enterprise

4
May 02, 2020

“Pipeline the group of activities”

This groups the activities into a unit that can perform a task in unison. For example, a pipeline containing a group of activities that ingests data from an Azure blob could run a Hive query on an HDInsight cluster for the partitioning of data.
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