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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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Awards

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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…

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  • Premium Consulting/Integration Services

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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
Avg 8.3

Data Transformations

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

8.5
Avg 8.1

Data Modeling

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

7.3
Avg 7.9

Data Governance

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

7.5
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 Connecto to Big Data and NoSQL and Simple transformations highest, with a score of 9.

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

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Reviews From Top Reviewers

(1-5 of 7)

Azure Databricks

Rating: 9 out of 10
June 03, 2022
GR
Vetted Review
Verified User
Azure Data Factory
2 years of experience
Orchestration platform for the Databricks notebooks. Have used an ETL for loading csv files into SQL server based database.
  • Orchestration engine
  • Low code Data pipeline
  • Logic apps integration
Cons
  • Error Flagging, Details of the error code is not specific especially faced this during Azure Table load
  • Missing feature of Data exploration functionality similar to Synapse Data explorer
  • missing access to orchestrate/create stream analytics job
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.

Simple Solution to Data Migration

Rating: 8 out of 10
June 22, 2021
Vetted Review
Verified User
Azure Data Factory
5 years of experience
We use Azure Data Factory to orchestrate ETL and ELT pipelines in our projects and it has a wide range of data connectors right from classic(FTP) and modern data lake storage like ADLS and AWS S3. Using the Dataflow and SSIS integration runtime server, it can perform complex transformations without the need for another tool. Executing and Monitoring ETL loads the data factory is very simple and user-friendly.
  • Orchestration
  • On premises support
  • Support to vast no of data connectors
  • Cloud migration
Cons
  • Native transform functions missing.
  • Pricing
  • Limited trigger functions.
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.

Azure Data Factory - Don't Abandon SSIS Just Yet

Rating: 7 out of 10
July 24, 2020
Vetted Review
Verified User
Azure Data Factory
1 year of experience
Azure Data Factory, particularly V2, offers a good option as a cloud-based ETL tool if you are leveraging the Azure cloud. We are using it as we begin to hybridize our on-prem data warehouse and applications with Azure. Up until now, we have leveraged SSIS for these purposes, but are beginning to migrate ETL and other data movement functions to the cloud, with Azure Data Factory as the primary utility.
  • Easy to set up and get started.
  • Runtimes make integration with on-prem data simple and also allow for support of existing investments in SSIS.
Cons
  • Limited source/sink (target) connectors depending on which area of Azure Data Factory you are using.
  • Does not yet have parity with SSIS as far as the transforms available.
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.

Database management and ETL tool for big data that is smart and reliable

Rating: 9 out of 10
June 05, 2021
NK
Vetted Review
Verified User
Azure Data Factory
1 year of experience
Get full data integration at scale with Microsoft Azure Data Factory's management service for serverless data integration,‌ hybrid data integration is easily and agilely possible through this software. We are creating ETL and ELT workflows as well as orchestrating and monitoring pipelines without writing any code. Full management and serverless integration with default features installed on the system and various connectors reduce costs. It is used in all company departments and project management units of our customers. Since ADF adopts an intelligent intent-driven mapping methodology, it enables copy activities to be automated.
  • Creating ETL and ELT workflows as well as orchestrating and monitoring pipelines without writing any code.
  • Hybrid data integration is easily and agilely possible through this software.
  • It has lot of various useful components
Cons
  • It should integrate more ETL and audit functionality.
  • Pipelines lack flexibility because moving Data Factory pipelines between different environments, such as for development or testing, require increased security and flexibility.
  • The number of pre-defined templates is small and they should have more variety.
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.

One of the best and reliable ETL & ELT platforms for pulling data from multiple sources

Rating: 10 out of 10
November 12, 2022
One of the best Data Integration tools for both ETL and ELT. I have been using ADF for the last 6+ years and it helped me in extracting several data feeds within our organization that meets our specific business needs. The tool provides many features such as Move and Transform, Data explorer, Azure Functions, Data bricks, Data Lake Analytics, Blob Storage, Linked services, Machine Learning, and Power Query.
  • It allows copying data from various types of data sources like on-premise files, Azure Database, Excel, JSON, Azure Synapse, API, etc. to the desired destination.
  • We can use linked service in multiple pipeline/data load.
  • It also allows the running of SSIS & SSMS packages which makes it an easy-to-use ETL & ELT tool.
Cons
  • For complex JSON when it comes to mapping nested attribute it's not easy to flatten out
  • Data Factory V1 does not have a good implementation experience as compared to V2
  • Work with on premise solutions sometimes is not too friendly because you will need to set a VPN
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.
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