

StreamSets and Fivetran compete in the data integration and pipeline management category. StreamSets holds an advantage in configuration flexibility and broad connector options, while Fivetran edges forward with user-friendly interfaces and managed data pipelines.
Features: StreamSets offers ease of configuration with a wide range of connectors allowing for robust data transformation and drift resilience. Its graphical data pipeline design tool supports both batch and streaming integration. Additionally, StreamSets minimally requires coding, which benefits less technically proficient teams. Fivetran excels in managed, seamless data replication and simple automation. Its integration with DBT for transformations and an easy setup process with an intuitive interface caters well to large data operations.
Room for Improvement: StreamSets faces challenges with non-Java platform integration, memory leak issues, and complicated logging mechanisms. Security gaps and limited SAP HANA features also need attention. Fivetran's high pricing, limited pipeline observability, and desire for more connectors are concerns. The tool's documentation and logs require enhancement, alongside customization options for hybrid environments.
Ease of Deployment and Customer Service: StreamSets supports deployment across public, hybrid, and on-premises environments, though user feedback suggests customer service response times are slow. Fivetran prioritizes public cloud and hybrid environments and is praised for simplicity and user experience, yet it lacks rapid support responses. Both platforms can improve user support, but Fivetran's easy deployment often reduces frustration.
Pricing and ROI: StreamSets utilizes a flexible CPU core-based licensing model with community and enterprise versions, noted for high costs but providing significant ROI through efficiency savings. In contrast, Fivetran's pricing may escalate with usage due to its data volume pricing model but is viewed as a worthwhile investment for larger operations due to its simplicity and scalability.
Fivetran provides time savings, cost reductions, and improvements in data quality.
It saves us the effort of having one to two data engineers managing the tasks that Fivetran handles.
If they could provide support more quickly, that would be great.
The technical support provided by Fivetran has generally been good, with a response time and competence that I would rate as good.
Customer support from Fivetran is quite good; it's really nice and responsive.
IBM technical support sometimes transfers tickets between different teams due to shift changes, which can be frustrating.
Fivetran's scalability has been tested effectively, and it has been working well for our organization's growing data needs.
They have 99.9% accuracy on the data load and they maintain transparency.
In my experience, Fivetran is stable with very few instances of downtime or reliability issues.
During the duration of the time that we used Fivetran, it was highly stable.
From a cost perspective, if the number of connectors is lesser, then Fivetran is not the most cost-efficient option.
When we tried to use a built-in Oracle connector, it didn't allow for the tweaks we needed, which led us to the SDK connector route and caused delays in development.
Fivetran could improve by adapting more for technical users and by providing more options for such users.
It would be beneficial if StreamSets addressed any potential memory leak issues to prevent unnecessary upgrades.
Our current yearly contract for Fivetran is approximately $70,000.
The most valuable feature of Fivetran is its built-in connectors for a wide range of data sources.
The real-time data replication is what I see best in the market where it reduces the overhead of customers needing to maintain the pipeline.
Fivetran not only has built-in connectors but also provides SDK connectors, allowing us to develop our own connectors in an easy manner.
It allows a hybrid installation approach, rather than being completely cloud-based or on-premises.
| Product | Mindshare (%) |
|---|---|
| Fivetran | 1.8% |
| StreamSets | 1.2% |
| Other | 97.0% |

| Company Size | Count |
|---|---|
| Small Business | 10 |
| Midsize Enterprise | 7 |
| Large Enterprise | 16 |
| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 2 |
| Large Enterprise | 11 |
Fivetran offers a seamless, scalable data integration platform with strong connectors and real-time synchronization. Tailored for managing ETL workflows and integrating with DBT, it appeals to organizations seeking efficient data management.
Fivetran distinguishes itself through its intuitive interface and extensive scalability, allowing businesses to manage entire ETL workflows seamlessly. Its robust connectors ensure smooth integration with multiple data sources, while transparent logging and minimal coding requirements enhance accessibility. With real-time data synchronization, organizations benefit from up-to-date insights for analytics and engineering purposes. While some users point out areas for improvement like better documentation and expanded integration options, Fivetran remains a cherished tool for centralizing data in data warehouses such as supporting change data capture, migrations, and synchronizations from systems like Salesforce, NetSuite, and Google Analytics. Operating within an ELT framework, it empowers businesses to streamline data processes without complex extraction logic.
What are the key features of Fivetran?In industry-specific implementation, Fivetran is integral for businesses requiring robust data integration to power analytics. Retailers utilize it to consolidate e-commerce data for sales insights, while finance firms rely on its capabilities to merge financial data for reporting. In the tech sector, it supports engineering teams by providing a reliable data pipeline that fuels app development and performance monitoring.
StreamSets streamlines data pipeline creation, connecting data from multiple sources to destinations like cloud platforms with minimal coding. Its centralized platform and intuitive design enhance ETL and data migration processes.
StreamSets integrates seamlessly with analytics platforms, offering tools such as Data Collector and Control Hub to facilitate data ingestion, transformation, and machine learning integrations. Its user-friendly interface and ready connectors aid in configuring complex data pipelines. With built-in data drift resilience and scheduling options, users experience efficient, scalable data management, despite challenges like latency in cloud storage and interface enhancement needs. Users often employ StreamSets for batch loading, real-time data processing, and smart data pipeline management, offering comprehensive data integration solutions.
What are the key features of StreamSets?In industries like finance and technology, StreamSets supports data migration, machine learning integrations, and analytics by simplifying data transformation and enhancing decision-making capabilities through its robust pipeline management.
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