Azure Data Factory and StreamSets compete in the data integration and ETL tools category. Azure Data Factory has the upper hand due to its integration within the Microsoft ecosystem and extensive built-in connectors.
Features: StreamSets offers no-code ETL capabilities, ideal for non-technical users, supports batch and streaming with data drift resilience and Change Data Capture. Azure Data Factory provides robust data transformation and integration with over 100 built-in connectors, favoring users with ETL process knowledge.
Room for Improvement: StreamSets faces integration challenges outside Java-based platforms and has a steep learning curve. Users raise concerns about logging and memory management. Azure Data Factory's complex pricing, limited streaming capabilities, and non-Microsoft platform integration require improvement. Documentation clarity and non-native system support are frequently mentioned.
Ease of Deployment and Customer Service: StreamSets is noted for excellent customer support but has a higher initial deployment effort due to its learning curve. It operates in public and hybrid cloud environments. Azure Data Factory leverages Microsoft's cloud infrastructure, easing deployment but complicating Azure resource management, often relying on community support.
Pricing and ROI: StreamSets offers diverse pricing from open source to enterprise, with higher costs for smaller businesses but notable ROI by reducing data drift issues. Azure Data Factory's pay-as-you-go model poses estimation challenges and can become costly with extensive use. Competitive pricing is noted, emphasizing careful management to prevent unexpected expenses.
The technical support from Microsoft is rated an eight out of ten.
The technical support is responsive and helpful
The technical support for Azure Data Factory is generally acceptable.
IBM technical support sometimes transfers tickets between different teams due to shift changes, which can be frustrating.
Azure Data Factory is highly scalable.
The solution has a high level of stability, roughly a nine out of ten.
Incorporating more dedicated API sources to specific services like HubSpot CRM or Salesforce would be beneficial.
There is a problem with the integration with third-party solutions, particularly with SAP.
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
It would be beneficial if StreamSets addressed any potential memory leak issues to prevent unnecessary upgrades.
The pricing is cost-effective.
It is considered cost-effective.
It connects to different sources out-of-the-box, making integration much easier.
The interface of Azure Data Factory is very usable with a more interactive visual experience, making it easier for people who are not as experienced in coding to work with.
I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets.
It allows a hybrid installation approach, rather than being completely cloud-based or on-premises.
Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.
StreamSets is a data integration platform that enables organizations to efficiently move and process data across various systems. It offers a user-friendly interface for designing, deploying, and managing data pipelines, allowing users to easily connect to various data sources and destinations. StreamSets also provides real-time monitoring and alerting capabilities, ensuring that data is flowing smoothly and any issues are quickly addressed.
We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
