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Azure Data Factory

Azure Data Factory

Overview

What is Azure Data Factory?

Microsoft's Azure Data Factory is a service built for all data integration needs and skill levels. It is designed to allow the user to easily construct ETL and ELT processes code-free within the intuitive visual environment, or write one's own…

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Recent Reviews
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Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

Popular Features

View all 11 features
  • Connect to traditional data sources (7)
    9.2
    92%
  • Simple transformations (7)
    9.2
    92%
  • Connecto to Big Data and NoSQL (7)
    9.0
    90%
  • Complex transformations (7)
    7.7
    77%

Reviewer Pros & Cons

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Pricing

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What is Azure Data Factory?

Microsoft's Azure Data Factory is a service built for all data integration needs and skill levels. It is designed to allow the user to easily construct ETL and ELT processes code-free within the intuitive visual environment, or write one's own code. Visually integrate data sources using more than…

Entry-level set up fee?

  • No setup fee

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

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Clear Analytics is a business intelligence solution that enables non technical end users to perform analytics by leveraging existing knowledge of Excel coupled with a built in query builder. Some key features include: Dynamic Data Refresh, Data Share and In-Excel Collaboration.

What is Vertify?

VertifyData is a cloud-based integration platform with core integration capacities, including a drag-and-drop interface and real-time synchronization. It also offers over 80 prebuilt connectors and templates, plus customizable integrations for scaling businesses.

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Features

Data Source Connection

Ability to connect to multiple data sources

9.1
Avg 8.2

Data Transformations

Data transformations include calculations, search and replace, data normalization and data parsing

8.5
Avg 8.4

Data Modeling

A data model is a diagram or flowchart that illustrates the relationships between data

7.7
Avg 8.2

Data Governance

Data governance is the practise of implementing policies defining effective use of an organization's data assets

7.7
Avg 8.2
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Product Details

What is Azure Data Factory?

A fully managed, serverless data integration service that enables users to visually integrate data sources with more than 90 built-in, maintenance-free connectors. Users can construct ETL (extract, transform, and load) and ELT (extract, load, and transform) processes, code-free or optionally with code. Integrated data can then be sent to Azure Synapse Analytics to unlock business insights.

Azure Data Factory Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo

Frequently Asked Questions

Microsoft's Azure Data Factory is a service built for all data integration needs and skill levels. It is designed to allow the user to easily construct ETL and ELT processes code-free within the intuitive visual environment, or write one's own code. Visually integrate data sources using more than 80 natively built and maintenance-free connectors at no added cost. Focus on data—the serverless integration service does the rest.

Reviewers rate Connect to traditional data sources and Simple transformations highest, with a score of 9.2.

The most common users of Azure Data Factory are from Enterprises (1,001+ employees).
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Comparisons

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Reviews and Ratings

(58)

Attribute Ratings

Reviews

(1-7 of 7)
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Score 9 out of 10
Vetted Review
Verified User
Incentivized
Well-suited Scenarios for Azure Data Factory (ADF):
When an organization has data sources spread across on-premises databases and cloud storage solutions, I think Azure Data Factory is excellent for integrating these sources.
Azure Data Factory's integration with Azure Databricks allows it to handle large-scale data transformations effectively, leveraging the power of distributed processing.
For regular ETL or ELT processes that need to run at specific intervals (daily, weekly, etc.), I think Azure Data Factory's scheduling capabilities are very handy.

Less Appropriate Scenarios for Azure Data Factory:
Real-time Data Streaming - Azure Data Factory is primarily batch-oriented.
Simple Data Copy Tasks - For straightforward data copy tasks without the need for transformation or complex workflows, in my opinion, using Azure Data Factory might be overkill; simpler tools or scripts could suffice.
Advanced Data Science Workflows: While Azure Data Factory can handle data prep and transformation, in my experience, it's not designed for in-depth data science tasks. I think for advanced analytics, machine learning, or statistical modeling, integration with specialized tools would be necessary.
Rajarshi Maitra PMI™- ASM®, ACP® and CAPM® | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
In a data pipeline, you will be able to add different kinds of activities for example connect from your on-premise SFTP and move CSV files to storage accounts. As well data factory has its own data flow if you are an ETL developer who experimented with maybe you have worked with SSIS, thus, you will start quickly with this new feature of the data factory.
June 03, 2022

Azure Databricks

Gorthy Rohith | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Well Suited:

  • Offers low code/no code features executes against spark pool.
  • Batch processing features, Tight coupling with Databricks & ETL jobs.
  • Offers Logic apps & Azure functions invoking API.
Less Appropriate:

  • Not much inherent features of Stream analytics (Liasing Azure Stream analytics to DF might be good option).
  • Advanced load options viz . Upsert type operations missing.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Azure Data Factory can perform better with Azure services and can easily do cloud migrations from on-premises services like SQL Server. It has a limited set of functionalities to transform data using SSIS integration services and data flow.
Niloofar Keshvari Nia | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
If you know a bit about database management everything is pretty easy, based on my personal experience. You can build a lot of things entirely in design, even if you do not know all the syntax, [since] having ready-made templates simplifies everything to get started and build the first pipeline.
Score 7 out of 10
Vetted Review
Verified User
Incentivized
If you are just getting started and all your data is resident in the Azure cloud, then Azure Data Factory is likely to work fine without having to jump through too many hoops. However, in a hybrid environment (which is most of them these days), ADF will likely need a leg up. It works well for scheduling and basic scheduling/orchestration tasks, but the feature set is not at a level with SSIS (which has been around for 15 years so...). As ADF now supports deploying SSIS, it is also a good candidate if large amounts of your data are resident in the Azure cloud and you have an existing SSIS investment in code and licensing. We are using it in a hybrid fashion for the data warehouse and will slowly transition over to ADF as the feature set improves. We are also using it for cloud-native applications that only require supplemental data from on-prem resources.
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