# Azure Data Factory Reviews **Vendor:** Microsoft **Category:** [Big Data Integration Platforms](https://www.g2.com/categories/big-data-integration-platforms) **Average Rating:** 4.6/5.0 **Total Reviews:** 99 ## About Azure Data Factory Azure Data Factory (ADF) is a fully managed, serverless data integration service designed to simplify the process of ingesting, preparing, and transforming data from diverse sources. It enables organizations to construct and orchestrate Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) workflows in a code-free environment, facilitating seamless data movement and transformation across on-premises and cloud-based systems. Key Features and Functionality: - Extensive Connectivity: ADF offers over 90 built-in connectors, allowing integration with a wide array of data sources, including relational databases, NoSQL systems, SaaS applications, APIs, and cloud storage services. - Code-Free Data Transformation: Utilizing mapping data flows powered by Apache Spark™, ADF enables users to perform complex data transformations without writing code, streamlining the data preparation process. - SSIS Package Rehosting: Organizations can easily migrate and extend their existing SQL Server Integration Services (SSIS) packages to the cloud, achieving significant cost savings and enhanced scalability. - Scalable and Cost-Effective: As a serverless service, ADF automatically scales to meet data integration demands, offering a pay-as-you-go pricing model that eliminates the need for upfront infrastructure investments. - Comprehensive Monitoring and Management: ADF provides robust monitoring tools, allowing users to track pipeline performance, set up alerts, and ensure efficient operation of data workflows. Primary Value and User Solutions: Azure Data Factory addresses the complexities of modern data integration by providing a unified platform that connects disparate data sources, automates data workflows, and facilitates advanced data transformations. This empowers organizations to derive actionable insights from their data, enhance decision-making processes, and accelerate digital transformation initiatives. By offering a scalable, cost-effective, and code-free environment, ADF reduces the operational burden on IT teams and enables data engineers and business analysts to focus on delivering value through data-driven strategies. ## Azure Data Factory Pros & Cons **What users like:** - Users value the **ease of automating complex data workflows** with Azure Data Factory, simplifying integration across various data sources. (7 reviews) - Users find the **ease of use** in Azure Data Factory invaluable for connecting and managing diverse data sources effortlessly. (7 reviews) - Users appreciate the **ease of connecting various data sources** , simplifying data integration and management across platforms. (6 reviews) - Users appreciate the **seamless data integration capabilities** of Azure Data Factory, simplifying complex workflows across various data sources. (6 reviews) - Users commend Azure Data Factory for its **scalability** , simplifying large data integration workflows with an intuitive interface. (5 reviews) - Users appreciate the **low code interface and integration flexibility** of Azure Data Factory for its usability and efficiency. (5 reviews) - Users benefit from the **automation capabilities** of Azure Data Factory, simplifying complex data integration and transformation tasks. (4 reviews) - Easy Integrations (4 reviews) - Flexibility (4 reviews) - Connectors Quantity (3 reviews) **What users dislike:** - Users often find **debugging difficult** in Azure Data Factory due to its limited troubleshooting tools and complexity. (5 reviews) - Users find **difficult debugging** a major challenge in Azure Data Factory, complicating their experience with complex pipelines. (4 reviews) - Users find Azure Data Factory **expensive** , especially with rising costs from large data volumes and frequent pipeline executions. (4 reviews) - Users find Azure Data Factory has **feature limitations** , hindering complex transformations and Power BI integration. (4 reviews) - Users find the **complexity** of Azure Data Factory overwhelming, especially with debugging and managing intricate workflows. (3 reviews) - Users report that **ADE's complexity** often leads to frustration, particularly when debugging and managing intricate workflows. (3 reviews) - Error Reporting (3 reviews) - Limitations (3 reviews) - Users find **complex processes** in Azure Data Factory overwhelming, particularly when debugging and managing intricate workflows. (2 reviews) - Users often experience **connectivity issues** with Azure Data Factory, leading to frustrating downtime during service outages. (2 reviews) ## Azure Data Factory Reviews ### 1. Low-Code Drag-and-Drop That Makes Development Easy for Developers and Business Users **Rating:** 4.5/5.0 stars **Reviewed by:** Shyam s. | Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** May 04, 2026 **What do you like best about Azure Data Factory?** The best part is its low-code/no-code (drag-and-drop) functionality. It makes development easier for developers and also makes the process more understandable for business users. **What do you dislike about Azure Data Factory?** Sometimes it’s hard to debug. I need to check why a record is not populated before the sink. Since all my tables have a lot of data, once I join them it becomes even more, and then it’s difficult to verify why a specific record isn’t coming through. To figure it out, I have to go back and change the source table, filter down to that record, and then see which join or filter isn’t working. That’s hard and time-consuming. The parameterization syntax is also an issue and can be difficult to work with. It would help if we had AI integration for this. **What problems is Azure Data Factory solving and how is that benefiting you?** We use it for ETL to migrate all source data to SQLMI. We also use it as an orchestration tool: we call the SQLMI procedures from there, and since our company is an enterprise, we have certain SSIS packages that are all orchestrated here as well. Overall, it’s a tool that helps us properly populate data in our warehouse. and from there we have outbound system salesforce and power bi where we have reports that helps for the daily discission in business ### 2. Intuitive, Scalable Data Integration with Azure Data Factory **Rating:** 4.5/5.0 stars **Reviewed by:** Alan R. | Software Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** March 09, 2026 **What do you like best about Azure Data Factory?** Azure Data Factory makes it much easier to build and manage data integration workflows in the cloud. The visual pipeline designer is intuitive and allows you to create complex data workflows without writing large amounts of code. It supports a wide variety of data sources and destinations, which makes integrating systems across databases, storage accounts, APIs, and SaaS platforms very straightforward. Another strong point is the scalability and reliability of the platform. Data pipelines can handle large volumes of data, and scheduling or triggering pipelines based on events is easy to configure. The integration with other Azure services like Azure Storage, Synapse, and monitoring tools also makes it a strong component of a modern data platform. **What do you dislike about Azure Data Factory?** Debugging and troubleshooting pipelines can sometimes be difficult. Error messages are not always very detailed, which can slow down the process of identifying issues. The UI is helpful, but complex pipelines can become harder to manage and visualize as they grow. Additionally, monitoring and cost tracking for large workloads requires careful attention, as pipeline executions and data movement activities can accumulate costs quickly. **What problems is Azure Data Factory solving and how is that benefiting you?** Azure Data Factory helps us automate and orchestrate data movement and transformation across multiple systems. Instead of building custom scripts or manual workflows, we can design pipelines that reliably move and process data on schedules or event triggers. This reduces operational overhead and ensures data is consistently available for analytics and reporting. It also improves scalability, as pipelines can handle increasing data volumes without requiring major infrastructure changes. ### 3. Review **Rating:** 3.5/5.0 stars **Reviewed by:** Elisa L. | Consultant Data&AI, Mid-Market (51-1000 emp.) **Reviewed Date:** April 29, 2026 ### 4. Azure Data Factory: Enterprise-Grade Orchestration with Practical, Reusable Pipelines **Rating:** 5.0/5.0 stars **Reviewed by:** Asad A. | Data Engineer, Computer Software, Enterprise (> 1000 emp.) **Reviewed Date:** January 30, 2026 **What do you like best about Azure Data Factory?** What I like best about Azure Data Factory (ADF) is that it hits a really nice spot between enterprise-grade orchestration and day-to-day practicality. A few highlights that genuinely stand out: Orchestration without friction: ADF is excellent at coordinating many moving parts: Blob storage, ADLS Gen2, Azure SQL, Synapse, Databricks, Functions, REST APIs, without forcing you to glue everything together manually. Pipelines, triggers, and dependencies feel very natural once you’ve used them a bit. Clear separation of concerns: The way ADF separates control flow (pipelines, activities, triggers) from data processing (Spark, SQL, Functions) is a big win. It doesn’t try to be the compute engine; it just orchestrates things cleanly and lets the right service do the heavy lifting. Parameterization & reusability: Pipelines, datasets, and linked services are highly parameterizable. This makes it easy to build config-driven ingestion frameworks (single pipeline, many sources), which scales really well in real enterprise setups. First-class integration with the Azure ecosystem: Native integration with Synapse, Key Vault, Event Grid, Functions, and Managed Identity is a huge plus. Secure access without secrets flying around is something you really appreciate in production. Operational visibility: Monitoring, retry logic, failure paths, and alerts are built in. When something breaks at 3 a.m., you can quickly see what failed, why, and with what input, without digging through logs for hours. Low barrier to entry, high ceiling: You can start with simple copy pipelines very quickly but still grow into advanced patterns: metadata-driven pipelines, conditional branching, dynamic execution, and hybrid solutions with Spark or Functions. **What do you dislike about Azure Data Factory?** ADF is an excellent tool at orchestration, but it can feel clunky for debugging, complex logic, and large-team development. **What problems is Azure Data Factory solving and how is that benefiting you?** Azure Data Factory (ADF) mainly solves the problem of coordinating complex data workflows across many systems, and that has been a big productivity win for me. What problems ADF solves? Disparate data sources: In real projects, data lives everywhere: cloud storage, databases, APIs, SaaS tools. ADF provides a single, consistent way to connect to and move data between all of them. Workflow orchestration complexity: Managing dependencies, schedules, retries, and failure handling across multiple jobs is hard. ADF centralizes this logic, so pipelines run in the right order with clear control flow. Environment and security management: Handling credentials, secrets, and access securely can get messy. ADF’s native integration with Managed Identity and Key Vault simplifies this significantly. Operational visibility: Without orchestration, it’s difficult to know what ran, what failed, and why. ADF gives built-in monitoring, logging, and alerting for data pipelines. Scalability and reliability: As data volumes and pipeline counts grow, manual or script-based approaches don’t scale well. ADF provides a managed, scalable service without needing to operate infrastructure. How this benefits me? I spend less time on glue code and scheduling logic, and more time on actual data modeling and transformation. Pipelines are repeatable, auditable, and production-ready, which is critical in enterprise environments. Failures are easier to detect and recover from, reducing operational overhead. I can design config-driven, reusable pipelines instead of one-off jobs, which improves maintainability and team collaboration. ### 5. Scalable, Secure Data Pipelines with 100+ Connectors and Strong Azure Integration **Rating:** 4.0/5.0 stars **Reviewed by:** Yuvashree M. | Senior Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** April 22, 2026 **What do you like best about Azure Data Factory?** Supports 100+ connectors (SQL, NoSQL, SaaS, Self-hosted IR). It offers scalable execution using Azure-managed compute, along with built-in monitoring, logging, and alerting. It also supports CI/CD with Azure DevOps and GitHub integration, and includes RBAC for secure access. **What do you dislike about Azure Data Factory?** Limited error details and fragmented logs make it harder to debug pipelines. Dependency management and error handling in pipelines can also get complex, especially across enterprise-scale implementations. **What problems is Azure Data Factory solving and how is that benefiting you?** In my project, we automated all enterprise-level client data flows using ADF, following best practices and implementing strong error handling. ADF solves key challenges around data integration, pipeline automation, and scalability. It also addresses the problem of data silos by enabling centralized orchestration and seamless integration across data sources and processes. ### 6. Component based ETL Tool and Connectivity **Rating:** 5.0/5.0 stars **Reviewed by:** Fabin P. | Senior Software Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** April 06, 2026 **What do you like best about Azure Data Factory?** It is easy to use, and component based which is good for us to learn quickly and also the multiple connectors **What do you dislike about Azure Data Factory?** This is good in all aspects but while it comes to compute or other storage aspects it would be more cost consumptions compared to other ETL tools. **What problems is Azure Data Factory solving and how is that benefiting you?** Azure Data Factory helps solve key challenges around data integration, orchestration, and automation across multiple systems. In many projects, data is spread across different sources like databases, APIs, and cloud storage, which makes it complex to manage and unify. ### 7. Effortless Data Integration and Automation with Azure Data Factory **Rating:** 4.0/5.0 stars **Reviewed by:** Dinesh G. | Lead Digital Cloud Architect - Hybrid Cloud, Small-Business (50 or fewer emp.) **Reviewed Date:** November 07, 2025 **What do you like best about Azure Data Factory?** What’s great about ADF is how easy it makes connecting all my different data sources whether they’re on-prem or in the cloud without having to write a lot of code. I can visually drag and drop to build complex data pipelines, automate repetitive data tasks, and seamlessly move and transform huge volumes of data as my projects grows. I can also monitor and manage everything from one place, which takes a lot of stress out of dealing with data integration and makes life much simpler for everyone involved. **What do you dislike about Azure Data Factory?** The things I dislike most about ADF are usually around its complexity and limitations. Debugging pipelines is often tricky and can be frustrating, especially when something fails, there aren’t many tools for step-by-step troubleshooting. If my workflow is complex, managing and understanding everything can get overwhelming with so many moving pieces and screens to keep track of. Additionally, its integration with non-Azure services is quite limited, so I may run into roadblocks if I need to connect other platforms or work in a Azure cloud setup. And while it handles simple tasks well, customizing things beyond standard connectors or data flows often means writing extra code or finding difficult workarounds. **What problems is Azure Data Factory solving and how is that benefiting you?** ADF helps to solve the headache of moving, combining, and transforming data from all sorts of different sources like databases, spreadsheets and cloud storage into one place where it’s actually useful. Instead of wasting my time setting up manual processes or dealing with multiple tools, I can automate everything and track it from a single dashboard. For me, this means less busywork, fewer errors, and a much easier time getting clean, reliable data for reporting or analysis, so I can focus more on my projects goals and less on chasing down technical hassles. ### 8. Easy, Scalable ETL Orchestration with Strong Azure Integration **Rating:** 5.0/5.0 stars **Reviewed by:** Ankit K. | Business Analyst, Information Technology and Services, Small-Business (50 or fewer emp.) **Reviewed Date:** March 12, 2026 **What do you like best about Azure Data Factory?** easy ETL pipeline orchestration, strong integration with Azure services, visual pipeline builder, scalable data movement, scheduling and monitoring features, good for cloud data migration **What do you dislike about Azure Data Factory?** debugging pipelines can be difficult, monitoring logs lack detail, UI can feel slow, complex pipelines become hard to manage, limited version control support **What problems is Azure Data Factory solving and how is that benefiting you?** automating ETL pipelines, orchestrating data workflows across services, simplifying cloud data migration, reducing manual data movement, improving data pipeline reliability ### 9. Effortless Data Integration and Pipeline Management with Azure Data Factory **Rating:** 4.5/5.0 stars **Reviewed by:** Abhishek B. | System Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** January 13, 2026 **What do you like best about Azure Data Factory?** A good things about Azure Data Factory is its easy integration with strong integration with veriety of data sources. Building pipelines are the easiest one, even for the complex workflows and monitoring data movement and failure is very convenient for day to day work. **What do you dislike about Azure Data Factory?** The only thing looks difficult about Azure Data Factory is debugging is not very user friendly sometimes. The errors/ issues are not clear always and complex pipeline become too difficult to manage. Ratio of pricing is depends on how optimised the pipeline used. **What problems is Azure Data Factory solving and how is that benefiting you?** Azure Data Factory coviently resolves issue of data integration and problems by moving and transforming data flow between different systems. Also it's benefits me by saving manual works, improving data readability and scheduled pipelines always available on time without any manual intervention for reporting and analytics for business. ### 10. Effortless Data Integration with Powerful Monitoring and Intuitive Transformations **Rating:** 4.5/5.0 stars **Reviewed by:** Daniel H. | Cloud Enginner, Telecommunications, Small-Business (50 or fewer emp.) **Reviewed Date:** January 09, 2026 **What do you like best about Azure Data Factory?** It enables scalable data integration between on-premises and cloud sources without intensive infrastructure management. Mapping data flows make complex transformations efficient and intuitive. I also appreciate the monitoring and control features, which provide clear visibility into pipeline executions. **What do you dislike about Azure Data Factory?** Debugging and error messages are not always clear, which can make troubleshooting time-consuming. Pricing can also be difficult to estimate, as the serverless model relies on activity execution and data movement. **What problems is Azure Data Factory solving and how is that benefiting you?** It eliminates the need for complex infrastructure by providing a scalable, serverless platform for moving and transforming data. Thanks to its low-code pipelines, it reduces development time and complexity, making it easier to create and maintain workflows. ### 11. Powerful, Scalable Data Integration with Azure Data Factory **Rating:** 4.5/5.0 stars **Reviewed by:** parth p. | Senior Cloud Engineer, Computer Software, Enterprise (> 1000 emp.) **Reviewed Date:** January 28, 2026 **What do you like best about Azure Data Factory?** Azure data factory is very powerful when it comes to data integration at scale from data sources like Azure blob storage and Azure SQL databases. The ability to create and run pipeline from SDK is also a very good feature to have implementation. **What do you dislike about Azure Data Factory?** The private networking setup is bit convoluted from administration standpoint. we had issues initially making Azure data factory working privately with rest of our Azure native resources. **What problems is Azure Data Factory solving and how is that benefiting you?** We majorly used Azure data factory for its data integration services to pre-process, clean, and transform our data for further use. Azure data factory's ease of use made it appealing choice against in-house build solution. ### 12. Effortless Data Integration with Powerful Automation and Scalability **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) **Reviewed Date:** January 11, 2026 **What do you like best about Azure Data Factory?** Its ability to orchestrate and automate complex data integration workflows at scale. Its low-code, visual interface makes it easy to build and monitor pipelines, while its seamless integration with a wide range of data sources—both on-premises and cloud—enables reliable end-to-end data movement. Additionally, features like built-in scheduling, monitoring, error handling, and integration with other Azure services make it a robust and scalable solution for enterprise data engineering needs. **What do you dislike about Azure Data Factory?** While Azure Data Factory is a powerful orchestration tool, some limitations include limited debugging capabilities for complex pipelines and the lack of advanced transformation features compared to dedicated data processing engines like Spark. Version control and CI/CD integration can also feel less intuitive, especially for large teams, and troubleshooting performance or runtime issues can sometimes require switching between multiple monitoring views. Additionally, costs can increase as pipelines grow in complexity and frequency, requiring careful optimization and governance. **What problems is Azure Data Factory solving and how is that benefiting you?** Azure Data Factory solves the problem of integrating data from diverse sources and orchestrating complex data workflows in a reliable and scalable way. It simplifies data ingestion, scheduling, and dependency management across cloud and on-premises systems, reducing manual effort and operational overhead. For me, this means faster pipeline development, consistent and repeatable data loads, better visibility into data movement through built-in monitoring, and the ability to focus more on data modeling and analytics rather than managing infrastructure or custom integration logic. ### 13. Essential for ETL and Data Ingestion with Seamless Integration **Rating:** 5.0/5.0 stars **Reviewed by:** Nishant A. | Cloud Architect, Civil Engineering, Enterprise (> 1000 emp.) **Reviewed Date:** January 07, 2026 **What do you like best about Azure Data Factory?** Azure Data Factories have been heavily implemented in our Organization and most of them are used for ETL/ELT, parsing data, etc I use the connectors for storage i.e. Blob and ADLS connector for data ingestion and data lake architecture. **What do you dislike about Azure Data Factory?** ADFs have latency hence real time streaming is an issue. **What problems is Azure Data Factory solving and how is that benefiting you?** I am using ADF to ingest raw files using storage Blob connector then move those files to ADLS bronze layer. ### 14. Flexible Scheduling, But Monitoring View Needs Improvement **Rating:** 5.0/5.0 stars **Reviewed by:** AMRUTRAJ H. | Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** October 31, 2025 **What do you like best about Azure Data Factory?** Schedules and various types of schedules available in ADF. **What do you dislike about Azure Data Factory?** We can’t see all our pipeline activities in single page while monitoring. Also data gets erased after 50 days **What problems is Azure Data Factory solving and how is that benefiting you?** Connecting to various sources to extract data with serverless option. This helps me in reducing cost and outsourcing infra. ### 15. Powerful , cloud native ETL made simple **Rating:** 4.5/5.0 stars **Reviewed by:** Shirisha D. | Infra transformation sr analyst, Enterprise (> 1000 emp.) **Reviewed Date:** October 07, 2025 **What do you like best about Azure Data Factory?** It's low code interface and integration flexibility is what I like best about azure data factory. You can connect to a wide range of data sources and create complex data pipelines visually without writing heavy code **What do you dislike about Azure Data Factory?** The debugging experience on the portal can be slow especially for large data flows. Also data flow mapping UI could be more responsive. **What problems is Azure Data Factory solving and how is that benefiting you?** Azure data factory helps automated and standardized our entire data pipelines from investing raw data to transforming and loading it into data warehouses. ### 16. User friendly **Rating:** 4.5/5.0 stars **Reviewed by:** Melissa R. | Test Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** September 04, 2025 **What do you like best about Azure Data Factory?** I find Azure Data Factory user friendly - it's easy to navigate and find what I am looking for. **What do you dislike about Azure Data Factory?** Nothing I particularly dislike - haven't used many similar tools. **What problems is Azure Data Factory solving and how is that benefiting you?** Software and data testing using storage containers. ### 17. Azure dafatory expert **Rating:** 3.5/5.0 stars **Reviewed by:** Ayrin G. | Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** October 07, 2025 **What do you like best about Azure Data Factory?** Orchestrating processes by using various activities within Data Factory. **What do you dislike about Azure Data Factory?** complex pipeline structure and hard to track **What problems is Azure Data Factory solving and how is that benefiting you?** Ingesting data from different servers, performing transformations, and building data marts, followed by the creation of business reports. ### 18. Serverless ETL Tool **Rating:** 2.5/5.0 stars **Reviewed by:** Vikram K. | Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** August 08, 2025 **What do you like best about Azure Data Factory?** Linked services to connect to all types of services **What do you dislike about Azure Data Factory?** Simple control flow becomes very complex to achieve **What problems is Azure Data Factory solving and how is that benefiting you?** Integration various sources at single platform to manage and trigger and control flow ### 19. Excellent ETL tool for Big Data work **Rating:** 5.0/5.0 stars **Reviewed by:** Aman Kumar K. | Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** October 25, 2024 **What do you like best about Azure Data Factory?** 1. Easy to use (Gives access to read data from multiple sources and data of multiple format) 2. Linked services gives lots of connection with other platform almost making it cross platform 3. Excellent ETL tool with lots of inbuilt activities. 4. Connection with Databricks notebook and it's integration is top class.(In case of complex ETL works we can use Databricks and call it directly to ADF pipeline) 5. Data Flow are easy to implement and very minimal code is required. **What do you dislike about Azure Data Factory?** Fails to perform complex transformation. Limitation of not able to perform more operations than Int32. **What problems is Azure Data Factory solving and how is that benefiting you?** We are migrating from On-prem data solutions to Cloud based data solutions and we are using Azure for it. Mainly ADF for ETL pipeline. Along with other sevices like Blob, ADLS, SQL Services, Databricks, Snowflake and Synapse. ### 20. Excellent Service **Rating:** 5.0/5.0 stars **Reviewed by:** Sowjanya G. | Digital Education Student Ambassador , Mid-Market (51-1000 emp.) **Reviewed Date:** September 18, 2024 **What do you like best about Azure Data Factory?** What I like best about Azure Data Factory is its robust and versatile data integration capabilities. It offers a wide range of connectors and tools to efficiently manage and transform data from various sources. Its user-friendly interface, combined with the flexibility to handle complex workflows, makes it an excellent choice for orchestrating data pipelines. The seamless integration with other Azure services also enhances its functionality, making it a powerful tool for data engineering tasks. **What do you dislike about Azure Data Factory?** The one aspect that could be improved is the cost management, if not carefully monitored, the expenses can add up quickly, particularly when dealing with large volumes of data or frequent pipeline runs. **What problems is Azure Data Factory solving and how is that benefiting you?** Azure Data Factory is solving the challenge of integrating and orchestrating data from diverse sources. It's particularly beneficial for creating and managing complex data pipelines, enabling seamless data movement and transformation across on-premises, cloud, and hybrid environments. This capability significantly reduces the manual effort required to handle large-scale data integration, ensuring that data is readily available for analysis and decision-making ### 21. ADF- Best Cloud ETL Tool **Rating:** 5.0/5.0 stars **Reviewed by:** MANISH P. | QA Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** December 31, 2024 **What do you like best about Azure Data Factory?** The best thing I like is its very easy to integrate with various Database and very easy to use the linked servies and also very affordable **What do you dislike about Azure Data Factory?** The ADF is very limited logging of pileine and monitoring the pipeline **What problems is Azure Data Factory solving and how is that benefiting you?** As we are Using Snowflake cloud Datawarehouse and its very easy to integrate with snowflake and It can handle lagre amount of data ### 22. Best & Easiest way to develop data pipelines **Rating:** 4.5/5.0 stars **Reviewed by:** Martand S. | Senior Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** October 30, 2024 **What do you like best about Azure Data Factory?** The easiness and the UI is the best among all other of it's competition. The UI is very easy and you create data pipeline in a a few click of buttons. The workflow allows you to perform data transformation which is again a drag-drop feature which allows new users to easily use it. **What do you dislike about Azure Data Factory?** I only thing which I think is missing is an easier way to integrate with power bi. I wish they could have provide more feature or easier way to refresh and load power bi semantic models. **What problems is Azure Data Factory solving and how is that benefiting you?** We are using data factory in aviation field to load data from operations, retails, sensors, operational stores to our enterprise level data platform. We are also using dataflow to transform data and also using data factory to call databricks pipelines. ### 23. Fastest Data Processing with Azure Data Factory **Rating:** 5.0/5.0 stars **Reviewed by:** Rajesh Y. | Manager, Enterprise (> 1000 emp.) **Reviewed Date:** May 20, 2024 **What do you like best about Azure Data Factory?** Azure data factory is great to use for data transformation. you can easily extract ,transform, load data using azure data factory. it has integration with clod and non cloud services and database. you can easily migrate your data of onprem to cloud using azure data factory. it has data flows , process which is very easy to use . Integration with any popular database is very easy. you can process files stored in any storage type and put the transformed data in any databse. Azure data factory has many inbuilt function which can be used for your data processing. you can easily process excel and CSV files data and perform operation like SQL very easy. Azure adoption is worldwise now. this can be used by any small and big organization easily. Customer support is also great. **What do you dislike about Azure Data Factory?** I am happy to use ADF. ADF just need to add more connectors with other third party data providors. Also logging can be improved further. **What problems is Azure Data Factory solving and how is that benefiting you?** It provides fatest data transformation without any issue. that is great thing. we used ADF to read content of blob storage data file and put in database. it saved our time and repeatative work. we used azure data factor to process blob storage files in databse. we used azure data factory for creating data set and data flow . we used Amazon rds vis linked services and craeted dataset. This dataset were as input and output for file processing. the great things about ADF that you can easily transform your data and we used to to put multi tenet data in one output data source. Apart from this we used ADF to load data from different datasource to central data source. we used in our organization and did data processing a lot. ### 24. Azure Data Factory review **Rating:** 5.0/5.0 stars **Reviewed by:** Shubham T. | Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** May 15, 2024 **What do you like best about Azure Data Factory?** One of the best and easy to use ETL tool by microsoft. It provide lots of feature like large number of source data connector,basic and advanced transformation option for better data integration,management and ingestion. It offer automated and manual method for executing or debugging pipeline which futher require less coding skills. Simple and interactive graphical user interface with high customer support. It is more benifical for small business as it is less expensive and offer more scalability option. **What do you dislike about Azure Data Factory?** As till now, I did not found any feature or option that I do not like about azure data factory ,everything is up to the need. **What problems is Azure Data Factory solving and how is that benefiting you?** Integrating data from multiple source,making advanced tranformationto it, is not easy task and it require more compatible and reliable tool or platform,for which I use Azure data factory as it is comaptible with other azure service and offer effective feature for data integration and transformation. ### 25. Azure data engineer **Rating:** 4.5/5.0 stars **Reviewed by:** Ashish S. | Senior database engineer, Enterprise (> 1000 emp.) **Reviewed Date:** March 11, 2025 **What do you like best about Azure Data Factory?** best ETL tool to handle big data. Sync data in report **What do you dislike about Azure Data Factory?** network issue in VM too long down time when service outage **What problems is Azure Data Factory solving and how is that benefiting you?** Dynamic data load and APi data load and performance DTU manage ### 26. Azure Data Factory Review **Rating:** 5.0/5.0 stars **Reviewed by:** Kamaljeet S. | Software Engineer, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2024 **What do you like best about Azure Data Factory?** It is a simple,easy to use ETL tool with high customer support. For data ingestion ,it can connect to multiple source like big data services files etc. Can also integrate with other azure services(like databricks,azure devops) with ease. It offer user friendly inteface to run or bebug pileline activities. It's has quite rich drag and drop features which futher require less coding skills . **What do you dislike about Azure Data Factory?** Sometime pileline execuition tooks more time as compare to the expected time due to some internal pipeline failure that are not easy to debug in ADF. Difficult to write complex transformation logic in ADF. **What problems is Azure Data Factory solving and how is that benefiting you?** To execute pipeline in Azure data factory require less efftorts by user because user just enter few parameters and after pipeline is executed automatically,therefore ADF save our time and provide more secure and reliable working efficiency. ### 27. An amazing one step solution for data intigration **Rating:** 4.5/5.0 stars **Reviewed by:** Anirban D. | Technical Lead, Enterprise (> 1000 emp.) **Reviewed Date:** April 01, 2024 **What do you like best about Azure Data Factory?** Most impressive feature of data factory is to impliment with multiple data source and multiple processing technique, Mostly the data looping part , where ican process data before migrating to new system, also visualizing the solution and drag drop option of feature makes it ultimate in this domain, **What do you dislike about Azure Data Factory?** One part i found little disappointing that inspite of having so many type of data connection . it is still not supporting to upload data to google bucket ,also trouble shooting pf problem should be more clear **What problems is Azure Data Factory solving and how is that benefiting you?** for our project we need to extract data from our sql server apply some logi to it for processing and then send it to multiple sources , the sources were sometime firestore database , sftp or sometime it was webapi also, we need a one step solution which can be easy for intigration as well as ll not be that much difficlut for opraation team to maintain, the easy intigration feature and supporting multiple destination connector in data factory solved this issue . now our ETL team can configure the pipeline and the operation team can run those easily whenever needed, which solves one of our biggest problem with very less effort ### 28. Azure Data Factory: Simple and best ETL tool ever **Rating:** 5.0/5.0 stars **Reviewed by:** Sanjana R. | Analyst, Mid-Market (51-1000 emp.) **Reviewed Date:** April 08, 2024 **What do you like best about Azure Data Factory?** First thing that I like about ADF is, it can connect to many data source like it may be big data services,azure data services,files ,warehouse etc. to ingest data to destination. Drag and drop features of ADF are very usefull and required less coding . Debugging and testing of pipeline activity is easy in ADF. Like the GUI of ADF platform . **What do you dislike about Azure Data Factory?** Proper Documentation of Azure Data Factory must be maintained by microsoft so that new user get basic idea about it. Due to less code feature,it is difficult to write complex transformation scripts. Sometime pipeline execution take more time as compared to required. To move user from dev to prod required understanding about CI/CD pipeline which is very complex. **What problems is Azure Data Factory solving and how is that benefiting you?** Connecting with multiple data source,and making transformation on it require more secure and reliable ETL tool which I think ADF is best for that. ### 29. Best ETL Tool in the Market **Rating:** 5.0/5.0 stars **Reviewed by:** Mohan N. | Programming Analyst - AIA Data. (Azure Data Engineer), Enterprise (> 1000 emp.) **Reviewed Date:** December 17, 2023 **What do you like best about Azure Data Factory?** ADF is cloud based Data integration tool on azure cloud. Its the fastest and best ETL tool out there comapred to onpremise and other cloud based ETL tool like Informatica, IICS, Talend, IBM datastage etc. It support so many connectors and lot of file formats. you can do so mant data integration transformation using ADF with ease and drag and drop features. Also you can view your data activities and its transformed data in real time instead of navigating each time to database and files like Azure sql server, oracle, JSON etc. it has awsome integration with big data tools like databricks, synapse analytics and blob storage. **What do you dislike about Azure Data Factory?** Microsoft done a great job to create this tool and there are nothing much but if the can provide more support to other different vendor connectors, databases for its transfromation activities as most of it only support to azure related storage. I mean there are few crucial activites like get metadata, until, stored procedure etc, although they are keep adding and supporting to new connectors in each update. **What problems is Azure Data Factory solving and how is that benefiting you?** We are using ADF to do data collection, extraction, transformation and loading purpose. also we are using it for scheduling the data pipelines with our business time. we getting data from mutiple sources specially heathcare raw data and it need some rules and transformation before going to into databases for business to do analytics and reporting. previously we were using the on premise informatica etl tool to all this but ADF is just lot better. ### 30. ADF an ETL Tool **Rating:** 5.0/5.0 stars **Reviewed by:** Utkarsh G. | Associate Cloud Infra & DevOps Engineer , Enterprise (> 1000 emp.) **Reviewed Date:** April 23, 2024 **What do you like best about Azure Data Factory?** The best features according to me are Hybrid Data Integration, Data Movement, Orchestration and Scheduling and Integration with other Azure Services. **What do you dislike about Azure Data Factory?** According to me there are no downsides of ADF. **What problems is Azure Data Factory solving and how is that benefiting you?** It helped me in moving data from various data sources like Blob storage, Amazon S3 and on-premises SQL servers. We can also scale up and scale down data integration pipelines according to demands. ### 31. Simplified ETL with powerful debugging **Rating:** 4.0/5.0 stars **Reviewed by:** Pranshu G. | Software Developer, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** September 12, 2023 **What do you like best about Azure Data Factory?** In my experience, ADF comes out to be a champion in its ease of use quality. The minimal coding requirements, drag and drop features has been incredibly useful. Not to mention the powerful debugging it offers. Its capabilities to integrate across various data sources is nothing but a life saver **What do you dislike about Azure Data Factory?** While ADF offers simplified ETL solution, it also creates challenges in few areas. Such as complex transformations using data flow. Debugging in Azure data flow has been a frustrating step in all my pipeline development. This particular feature is rather inefficient when it comes to transform huge volume of data. Add in ambiguous errors and you got your biggest nightmare **What problems is Azure Data Factory solving and how is that benefiting you?** It helped in creating scalable ETL pipelines. I have also used it integrating with Databricks as well as Salesforce API. It also helped in automating the entire databricks notebooks making data processing more robusts and efficient ### 32. Reviewing azure data factory **Rating:** 4.5/5.0 stars **Reviewed by:** Myo Min H. | Azure Data Engineer, Financial Services, Mid-Market (51-1000 emp.) **Reviewed Date:** June 08, 2023 **What do you like best about Azure Data Factory?** 1. ADF can handle large volumes of data and support diverse formats. Whether it is RDBMS, NoSQL,File system, app or services, we can connect with them to ADF and do complex data processing, data integration. 2. visual workflow orchestration simplifies the creation and management of complex data pipelines. It is very easy to build a pipeline in the Azure data factory. Drag-and-drop features make it simple for the user. Plus, every pipeline structure that we have built is written in JSON format which is really amazing when it comes to changing and copying the pipeline structure from one ADF to another ADF. 3.the integration with Azure services like Azure Data Lake Storage, Azure Synapse Analytics, and Azure Databricks enhances our data engineering pipeline's overall capabilities and productivity. **What do you dislike about Azure Data Factory?** 1.Microsoft should improve on ADF documentation and availability of comprehensive examples and tutorials for different scenarios. Different companies have different scenarios and different pipeline structure.In order to to customize what they want, ADF should provide more basic documentation and tutorials that are sharing across orgs. 2. Sometimes it has bugs when we are duplicating one data pipeline and replace necessary datasets and linked service in duplicated one. When we run duplicated pipeline, it is still cached the previous data pipeline and can’t see the duplicated data. That time, we have to refresh the browser which is annoying and time-consuming. **What problems is Azure Data Factory solving and how is that benefiting you?** We have data coming from facebook chatbot. We collect the raw data in azure SQL database. With the help of Azure Data Factory, we build pipelines for data transformation,data processing and loading the transformed data to repsective tables. ### 33. ADF Review **Rating:** 4.5/5.0 stars **Reviewed by:** Dinesh S. | G2 member, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** October 12, 2023 **What do you like best about Azure Data Factory?** It hekps in design a pipeline using different functionalities that can accomodate source and target location and implement the function based on the pipeline created.Also it has execllent feature like monitoring the pipeline and have an option to rerun the pipeline which reduces the rework on creating a duplicate data refresh pipeline. **What do you dislike about Azure Data Factory?** It requires a basic knowledge on the app on how to create the pipeline ,how we can access the datalake storage areas and map it to the source and sink on the new pipeline. **What problems is Azure Data Factory solving and how is that benefiting you?** The pipeline helps us in refreshing the data which runs at short interval of time even for millions of data. ### 34. The best cloud ETL tool with visual data integration services and other script can be used. **Rating:** 5.0/5.0 stars **Reviewed by:** Vikas K. | ETl developer, Enterprise (> 1000 emp.) **Reviewed Date:** October 23, 2023 **What do you like best about Azure Data Factory?** The best thing in ADF is the data flow debug where we can direct check the data flow output in every task and find the errors with pipeline run. **What do you dislike about Azure Data Factory?** Deployment to prod but it's not too dislike but it's hard to deploy to prod from dev . We have to use cl cd pipelines etc. **What problems is Azure Data Factory solving and how is that benefiting you?** Creating a fully functional enterprise Data Warehouse and we are using Azure services and we have used ADF as ETL tool and it was very easy to implement SCD Types and other data integration. ### 35. ADF: A great tool **Rating:** 5.0/5.0 stars **Reviewed by:** Himani S. | Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** June 14, 2023 **What do you like best about Azure Data Factory?** Data Integration and Orchestration: ADF allows you to efficiently integrate and orchestrate data from various sources, both on-premises and in the cloud. It provides a visual interface for designing data pipelines, making it easier to define and manage complex data integration workflows. Broad Data Source Support: ADF supports a wide range of data sources, including Azure services, on-premises databases, SaaS applications, and various file formats. This flexibility enables you to extract, transform, and load (ETL) data from diverse sources, making it suitable for heterogeneous data environments. Scalability and Performance: ADF leverages the scalability and power of the Azure platform to handle large volumes of data and process it at scale. It can parallelize data processing activities, optimize resource utilization, and provide efficient data movement capabilities, leading to improved performance. **What do you dislike about Azure Data Factory?** Till now I havnt found any cons of ADF in my 4 years of IT experience wotking with ADF **What problems is Azure Data Factory solving and how is that benefiting you?** It helped the clients all accros the world to save a large amount of money ### 36. Data Factory for Analysts **Rating:** 3.0/5.0 stars **Reviewed by:** Ravindra J. | Consultant, Enterprise (> 1000 emp.) **Reviewed Date:** May 09, 2023 **What do you like best about Azure Data Factory?** The most helpful thing is that it helps in loading huge amounts of data with just a trigger of a pipeline and a job. It is on the cloud and base don microsoft it becomes easy **What do you dislike about Azure Data Factory?** SOmetimes it becomes difficult to comprehend the errors due to which the data pipeline fails. Even after looking on internet doesn't help so may be the error message can be improved which helps users to comprehend and easily resolve it. **What problems is Azure Data Factory solving and how is that benefiting you?** as I mentioned earlier, we use Azure Data Factory for loading huge amounts of data which is modelled in Analysis Services model. So, we have alreadys et up the pipelines/jobs and every night those run to provide the updated data the next day ### 37. Azure Data Factory review **Rating:** 4.5/5.0 stars **Reviewed by:** Dhiraj M. | Senior Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** July 05, 2023 **What do you like best about Azure Data Factory?** It is easy to use for data engineers because of its drag and drop feature. Its a powerful no code etl tool. it can easily perform orchestration and can build robust data engineering pipelines. **What do you dislike about Azure Data Factory?** Due to its no code feature there is a limitation in doing complex transformations in it. And also CI/CD of data factory pipelines is very complex as chery picking is not available. **What problems is Azure Data Factory solving and how is that benefiting you?** Its a very useful tool for creating data engineering pipelines end to end with the use of various connectors and components. Its a very powerful orchestration tool. ### 38. Easy orchestration and development **Rating:** 4.5/5.0 stars **Reviewed by:** Drishti C. | Data Analyst, Mid-Market (51-1000 emp.) **Reviewed Date:** November 02, 2023 **What do you like best about Azure Data Factory?** Easy UI, love the transformation building using data flow. Easy integration with data bricks and api gateways **What do you dislike about Azure Data Factory?** nothing really. More ease with global parameters **What problems is Azure Data Factory solving and how is that benefiting you?** Easy ETL without coding. Also, global parameters are amazing ### 39. A good ETL/ELT tool on Azure cloud **Rating:** 4.0/5.0 stars **Reviewed by:** Vaibhav P. | Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** June 09, 2023 **What do you like best about Azure Data Factory?** The Best thing about ADF is we can integrate almost every data source into it. I liked the Data flows the most as it provides a Spark engine, and we can debug and preview the data without actual execution. **What do you dislike about Azure Data Factory?** The pane where we create pipelines and data flows requires a big screen and becomes complicated if we add more components in the pipeline on a small screen device. **What problems is Azure Data Factory solving and how is that benefiting you?** We use ADF to load data from SAP APIs using Azure logic apps into Azure blob storage. Further, we load the data from blob storage to our on-premise database and perform the transformations using Informatica PowerCenter. ### 40. Excellent data orchestration service **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** November 24, 2023 **What do you like best about Azure Data Factory?** Best platform to control and orchestrate data flows from different wide sources and able to connnect differnt azure service using linked services **What do you dislike about Azure Data Factory?** Not able to transfer data to virtual machines **What problems is Azure Data Factory solving and how is that benefiting you?** Simplify connectivity to on premise data sources and provide full control over the data flows and monitoring services ### 41. Review on Azure Data Factory **Rating:** 4.5/5.0 stars **Reviewed by:** Shilpi J. | Senior Software Development Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** August 04, 2023 **What do you like best about Azure Data Factory?** I worked as a developer on a spark project where we process large amount of data using Azure data factory. It process data very fast and in efficient way. Also it supports a number of data sources. **What do you dislike about Azure Data Factory?** While working on a spark project I faced some challenges on advanced data processing tasks like filtration. On those lines it can be improved further. **What problems is Azure Data Factory solving and how is that benefiting you?** It solves the challenges of processing large data very fast & in efficient way. also provides a lot of transformation capabilities along with multiple data sources that we can use while copying and other operations. ### 42. Achieving collaboration and integrated management of diverse data in the cloud **Rating:** 4.5/5.0 stars **Reviewed by:** Marian C. | Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** April 18, 2023 **What do you like best about Azure Data Factory?** Azure Data Factory is a cloud service for data integration management that collects and links diverse data. It will be easier to understand if you imagine a line that trades immediately with collected and accumulated data (materials and raw materials). In addition, it can be linked to various systems to automate multiple information extraction processes required for data analysis. It can also be used for data integration, such as ETL and ELT. Azure Data Factory allows linking and using fragmented data through the development of ICT, accelerating the diversification of systems used in the enterprise from on-premises to the cloud. This platform makes business more efficient and convenient, as data is accumulated, analyzed and used efficiently, i.e., centrally managed. Transforms collected and stored data. Allows data to be used in a unified format to create graphs. **What do you dislike about Azure Data Factory?** I like Azure Data Factory because it can be used for conventional ETL and ELT with a few mouse clicks, as it can be flexibly scaled horizontally and vertically. **What problems is Azure Data Factory solving and how is that benefiting you?** With the generalization of computing and ICT in companies, all kinds of information have become data. However, systems often store a combination of various data formats, such as text data, image data and video data. Azure Data Factory's ability to centralize data is critical, as companies increasingly use big and disorganized data. In the past, the overall storage capacity was small, and the amount of data collected at one time was small, so it was common to process in the order of data, extraction, conversion/processing, storage, and ETL used. However, now that Azure Data Factory, the large-capacity warehouse, is available, it is possible to store the raw data before processing and converting it, so the data extraction, storage, conversion/processing, and ELT method is also used. ### 43. Best ETL Tool **Rating:** 5.0/5.0 stars **Reviewed by:** Swetha Y. | Senior Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** May 31, 2023 **What do you like best about Azure Data Factory?** The best thing is that it have lot of connectors for many on- premise servers and cloud servers and best part is data factory UI, where we can design complex etl pipelines by simply drag and drop the activities . **What do you dislike about Azure Data Factory?** I haven't faced any challenges with ADF , however there are some limitations where we can't perform some activities directly like nested control and also for complex transformation Adf mapping data flows not that much effective, but it's a best product. **What problems is Azure Data Factory solving and how is that benefiting you?** We use ADF to built ETl pipelines which will apply the transformations on financial data at one place and load them to Azure synapse i.e data warehouse and also help us to schedule jobs based on event based and removed the manual intervention. ### 44. Best Data Orchestration tool in the Market **Rating:** 5.0/5.0 stars **Reviewed by:** Neelesh Kumar I. | Manager, Enterprise (> 1000 emp.) **Reviewed Date:** November 02, 2023 **What do you like best about Azure Data Factory?** Implementing pipelines is very easy as it drag and drop **What do you dislike about Azure Data Factory?** connectivity datasources which only allow JWT is challenging and some data scenarios cannot be implemented **What problems is Azure Data Factory solving and how is that benefiting you?** Very effective and efficient tool for intergrating with mutiple Big data platforms. Helps resolve Big data management problems in a effective way. ### 45. An excellent tool for managing and transforming data **Rating:** 5.0/5.0 stars **Reviewed by:** Shaun B. | Solution Engineer / Client Sales Support IV, Small-Business (50 or fewer emp.) **Reviewed Date:** September 13, 2022 **What do you like best about Azure Data Factory?** We use Azure data factory to pull data from multiple sources and import it into our data warehouses. We have many disparate data sources that rarely share a similar format. Using ADF, we can pull in the data automatically, normalize it, run queries against the current DW, import it into our DW, and archive files in cold storage. It's truly a lifesaver for anyone who prefers points and clicks to code. **What do you dislike about Azure Data Factory?** The learning curve can be pretty steep to learn how to use ADF. I used YouTube videos to supplement my knowledge, which was quite helpful. Once you get the concepts down, it's easy to apply to other projects, but finding out where to start can sometimes be daunting. **What problems is Azure Data Factory solving and how is that benefiting you?** We use it to transform and load data into our DW. We have plans in the future to also use it for lots of other projects, but the primary use case was to load data. ### 46. Easy To Use For ETL Purpose **Rating:** 4.0/5.0 stars **Reviewed by:** Prashant S. | Consultant, Enterprise (> 1000 emp.) **Reviewed Date:** August 09, 2022 **What do you like best about Azure Data Factory?** Adf is an ETL tool provided by MS the best thing that I like is it is easy to use and we can easily connect this using link services with third-party resources to fetch the data. We can create a separate dataset for source and sink and using pipeline activity we can implement any transformation and get the required result using the sink directory. We have direct connectivity with databricks using the dbx workspace token we can connect our databricks notebooks using ADF. **What do you dislike about Azure Data Factory?** There is no major dislike but some points that I wanted to highlight are it has limitations in one pipeline we can create up to 40 activities and sometimes I faced any kind of strange error or a low server pipeline gets automatically failed without any hard reason so sometimes if we have prescheduled pipeline it may cause the data loss. **What problems is Azure Data Factory solving and how is that benefiting you?** ADF is mainly used to fetch data from third party sources. If the client has data in their on-prem system then ADF has advanced connectivity for this which is self-hosted integration runtime using this IR we can easily connect that VM with ADF and fetch the data. I used ADF to fetch the results using API's also a lot of API sources where we don't have direct connectivity using rest API or web activity we can fetch the data through adf by providing correct credentials. I used adf for logic app connectivity also where we can refresh power bi dashboard or call any api to push status mail. ### 47. Great use for migration of data using pipeline **Rating:** 4.0/5.0 stars **Reviewed by:** Ajinkya D. | Associate Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** February 25, 2023 **What do you like best about Azure Data Factory?** Ease to making and deploying the data pipeline in Azure Data factory and best for all migration of large of amount of database . **What do you dislike about Azure Data Factory?** Not for beginners' use, and also it's taking lots of time for migration **What problems is Azure Data Factory solving and how is that benefiting you?** Making more straightforward migration of any source is more accessible than much and easier with the best dataflow ### 48. Greatest powerful tool I've used so far is Azure Data Factory!! **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) **Reviewed Date:** January 14, 2023 **What do you like best about Azure Data Factory?** The best part of the azure data factory is we can perform various tasks like copy data from one platform to azure just like that. E.g Database replication, S3 bucket to azure blob storage.etc. It has the jobs which we can schedule based on our requirement and the drag and drop features which makes the UI and Administrator to easily work on the data factory **What do you dislike about Azure Data Factory?** We haven't faced any challenges with DataFactory. However, we are looking for more integration option must available. **What problems is Azure Data Factory solving and how is that benefiting you?** We have been into migrating our data where the data factory played a major role in our migration project. ### 49. One of the best cloud data pipelining tool with very minimal coding and multiple connectors **Rating:** 5.0/5.0 stars **Reviewed by:** Biswajeet S. | Data Analyst GAMMA, Enterprise (> 1000 emp.) **Reviewed Date:** October 07, 2022 **What do you like best about Azure Data Factory?** In Azure data factory I like most about it's data pipeline feature, synapse, databricks, storage account and all type of connectors, and it has the best scheduler where any non-programmer also can create pipeline and schedule **What do you dislike about Azure Data Factory?** Nothing in dislike, if ADF resource price can reduce then it would be great and if sandbox account also gets ADF resource that would be also best to test and practice. Rest it's a best data pipeline product **What problems is Azure Data Factory solving and how is that benefiting you?** For our retail clients, we use ADF in many ETL and data pipelining projects. ADF is mainly used to apply the transformation on different ERP, Sales, Finance and all departmental store data at one place and send them to data warehouses. ### 50. Review on Azure Data Factory **Rating:** 5.0/5.0 stars **Reviewed by:** Arijit C. | Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** August 09, 2022 **What do you like best about Azure Data Factory?** It helps to orchestrate different jobs through pipeline creation. Also, various environments can be connected easily through ADF, and the no code environment makes it easier. **What do you dislike about Azure Data Factory?** Azure Data Factory doesnt allow you to send customized mails based on the failed activity. If any activity of a pipeline fails, it will send a mail that the pipeline has failed, but doesnt mention which activity has failed. **What problems is Azure Data Factory solving and how is that benefiting you?** Its helps us to schedule jobs based on a specific time or event based. It also helps to orchestrate various activities and thus removies the manual dependency a lot. ## Azure Data Factory Discussions - [Is Azure data Factory an ETL tool?](https://www.g2.com/discussions/is-azure-data-factory-an-etl-tool) - 2 comments - [View Azure Data Factory pricing details and edition comparison](https://www.g2.com/products/azure-data-factory/reviews?section=pricing&secure%5Bexpires_at%5D=2026-05-14+04%3A27%3A20+-0500&secure%5Bsession_id%5D=e5dfce13-2927-4bb1-81bb-4d2c6ba5179d&secure%5Btoken%5D=a2f27851f0848f8e59496b094cc0646a614780a1b7572d51d9b7cf872c82de3f&format=llm_user) ## Azure Data Factory Integrations - [Agentforce Sales (formerly Salesforce Sales Cloud)](https://www.g2.com/products/agentforce-sales-formerly-salesforce-sales-cloud/reviews) - [Amazon Simple Email Service (Amazon SES)](https://www.g2.com/products/amazon-simple-email-service-amazon-ses/reviews) - [Azure Blob Storage](https://www.g2.com/products/azure-blob-storage/reviews) - [Azure Databricks](https://www.g2.com/products/azure-databricks/reviews) - [Azure Data Lake Store](https://www.g2.com/products/azure-data-lake-store/reviews) - [Databricks](https://www.g2.com/products/databricks/reviews) - [Google Ads](https://www.g2.com/products/google-ads/reviews) - [Microsoft Power BI](https://www.g2.com/products/microsoft-microsoft-power-bi/reviews) ## Azure Data Factory Features **Management** - Reporting - Auditing **Functionality** - Extraction - Transformation - Loading - Automation - Scalability ## Top Azure Data Factory Alternatives - [SnapLogic Intelligent Integration Platform (IIP)](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews) - 4.4/5.0 (370 reviews) - [dbt](https://www.g2.com/products/dbt/reviews) - 4.7/5.0 (204 reviews) - [AWS Glue](https://www.g2.com/products/aws-glue/reviews) - 4.3/5.0 (191 reviews)