

Denodo and Fivetran are prominent players in the data management sector. Denodo takes the edge with its advanced data virtualization capabilities, effectively coupling various data sources, while Fivetran offers straightforward data replication with managed pipelines for easy synchronization.
Features: Denodo offers robust integration capacities, a powerful semantic layer, and seamless coupling of diverse data sources, providing structured data access without data movement. Fivetran excels in data replication, managed pipelines for easy integration with business applications, and seamless synchronization capabilities.
Room for Improvement: Denodo users seek enhanced functionality in the data catalog, better integration with metadata systems, and more accessible support documentation. Fivetran users call for improved data pipeline observability, comprehensive support beyond chat platforms, and more transparent pricing with additional data connectors.
Ease of Deployment and Customer Service: Denodo supports on-premises, hybrid, and private cloud deployments but needs better training materials, with varied customer support experiences reported. Fivetran focuses on cloud-based deployment, providing strong technical support and direct developer access, though pricing practices raise concerns.
Pricing and ROI: Denodo's pricing, though seen as high by some, provides a positive ROI within six months due to efficiency gains. Fivetran's cost model, especially for extensive data use, is considered expensive. Negotiable pricing and economies of scale, however, offer increased affordability and significant ROI through enhanced data efficiencies.
It provides a positive return on investment for those who can connect multiple data sources and make data-driven decisions easily.
If you don't need to write a whole ETL to make the data virtualization, you need way fewer people to write a query instead of writing an ETL pipeline.
I have seen a return on investment, which showed up in improved customer satisfaction scores.
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.
They have a good methodology for learning how to use the tool.
Denodo's customer support team is very competent and responsive.
If we raise a ticket, it can be resolved or addressed within a reasonable time frame, so support is good.
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.
For huge data requests, it cannot scale automatically; admin action is required.
Denodo's scalability comes into play specifically when there is data transfer.
My client has almost 100 million records, and the performance was impacted in a way that required optimization.
Fivetran's scalability has been tested effectively, and it has been working well for our organization's growing data needs.
I would rate it nine out of ten because it is very reliable, always performing as expected.
If JVM does not function properly, it may cause Denodo to fail to connect to different sources.
Denodo is stable and good.
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.
Ensuring data caching is up to date is critical.
Denodo needs better communication on how the product can be deployed for specific solutions.
The system has dependencies on other environments, like JVM, which can affect its performance.
From a cost perspective, if the number of connectors is lesser, then Fivetran is not the most cost-efficient option.
I want more flexibility during ingestion, specifically for transformations needed beforehand.
Fivetran could improve by adapting more for technical users and by providing more options for such users.
For small companies, it's not a solution that most small companies can afford.
Denodo is considered pricey, limiting its use to large enterprises or government organizations that can afford its comprehensive setup.
Denodo's pricing is not affordable for small companies and is more suitable for medium to large enterprises.
Our current yearly contract for Fivetran is approximately $70,000.
Denodo's ability to connect to multiple data sources and perform extract-transform-load (ETL) operations on the fly is noteworthy.
The most valuable feature of Denodo is its uniformity of self-site data access types, which allows it to connect to almost any storage technology and feed it transparently.
Denodo supports SQL base, so if you want to join two tables or two views, you can use SQL, which is an advantage as most developers or business people know SQL.
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.
The ability to seamlessly integrate with a large variety of data sources is valuable.
| Product | Mindshare (%) |
|---|---|
| Denodo | 1.4% |
| Fivetran | 1.8% |
| Other | 96.8% |


| Company Size | Count |
|---|---|
| Small Business | 16 |
| Midsize Enterprise | 6 |
| Large Enterprise | 21 |
| Company Size | Count |
|---|---|
| Small Business | 10 |
| Midsize Enterprise | 7 |
| Large Enterprise | 16 |
Denodo specializes in data virtualization, data cataloging, and user-friendly interfaces. It's recognized for connecting disparate data sources, presenting unified data for analytics, and supporting efficient decision-making with agile analytics and robust data governance.
Denodo effectively aggregates data from multiple sources to offer a comprehensive understanding through its virtualization capabilities. It provides role-based access control, flexible query languages, performance optimization, and integration with databases. Enhancements are needed in its interface and documentation to ensure better user experiences. While the platform supports cloud migration, integration challenges with tools like Salesforce and MuleSoft exist. Improvements in data visualization, automation, and scalability, especially in large data environments, are critical areas for growth.
What are the key features of Denodo?In industries like finance, healthcare, and retail, Denodo plays a crucial role in data virtualization and integration. Organizations use it to unify disparate data systems, enabling real-time analytics and supporting cloud migrations. Denodo's platform is ideal for businesses needing to aggregate, transform, and utilize diverse data efficiently, optimizing operations and enhancing governance.
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.
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