

Denodo and AWS Glue compete in the data integration and data virtualization category. Denodo appears to have an advantage in data virtualization and integration capabilities, while AWS Glue has the upper hand in seamless integration with AWS services and serverless capabilities.
Features: Denodo is preferred for its strong data virtualization features, allowing data abstraction and integration with multiple sources, including flat files and cloud databases, without moving data physically. AWS Glue stands out for its serverless architecture and smooth AWS services integration, offering a flexible data processing interface, efficient ETL features, and a robust data catalog.
Room for Improvement: Denodo users suggest enhancements in data catalog capabilities, improved connectivity, and better integration with metadata systems, alongside more comprehensive support and documentation. AWS Glue could benefit from improved user-friendliness, more intuitive documentation, and a smoother experience for non-technical users. Concerns include high costs, rigid pricing structure, and integration challenges with non-AWS tools.
Ease of Deployment and Customer Service: Denodo supports various deployment models such as on-premises, hybrid, and cloud, offering flexibility but sometimes faces integration challenges and mixed customer support reviews. AWS Glue excels in cloud environments and benefits from the AWS ecosystem, yet could improve in responsive support and ease of use for new AWS users. Its deployment is straightforward for existing AWS users but can present a learning curve for newcomers to AWS services.
Pricing and ROI: Denodo can be expensive and often structures pricing on CPU usage, posing predictability challenges, but offers ROI through improved processing times and decision-making abilities. AWS Glue's pay-as-you-go model supports scalability but may incur higher costs during peak usage, justifying expenses through efficient AWS integration. While ROI is visible in data processing, initial costs might be a hurdle for smaller businesses.
I advocate using Glue in such cases.
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.
Upgrades occur every four months, and new developments coincide with version updates.
For complex Glue-related problems such as job failures or permission issues, their documentation is good, but having direct access to support helps cut down troubleshooting time significantly.
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.
It is beneficial to upgrade jobs, and we conduct extensive testing in development before migrating to production.
It can easily handle data from one terabyte to 100 terabytes or more, scaling nicely with larger datasets.
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.
AWS Glue is highly stable, and I would rate its stability as nine.
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.
Migrating jobs from version 3.0 to 4.0 can present compatibility issues.
With AWS, I gather data from multiple sources, clean it up, normalize it, de-duplicate it, and make it presentable.
A more user-friendly and simpler process would help speed up the deployment process.
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.
Costing depends on resource usage, and cost optimization may involve redesigning jobs for flexibility.
AWS charges based on runtime, which can be quite pricey.
The smallest cost for a project is around €700, while the largest can reach up to €7,000 based on the scale of the usage.
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.
For ETL, I feel the performance is excellent. If I create jobs in a standard way, the performance is great, and maintenance is also seamless.
AWS Glue's most valuable features include its transformation capabilities, which provide data quality and shape for processing in ML or AI models.
AWS Glue has reduced efforts by 60%, which is the main benefit.
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.
| Product | Mindshare (%) |
|---|---|
| AWS Glue | 7.6% |
| Denodo | 3.2% |
| Other | 89.2% |

| Company Size | Count |
|---|---|
| Small Business | 11 |
| Midsize Enterprise | 6 |
| Large Enterprise | 32 |
| Company Size | Count |
|---|---|
| Small Business | 16 |
| Midsize Enterprise | 6 |
| Large Enterprise | 21 |
AWS Glue is a serverless data integration service offering seamless integration with AWS services like S3, Redshift, and Athena. Known for its flexibility with data formats and automation of ETL tasks, AWS Glue enhances data management and transformation.
AWS Glue facilitates seamless data extraction, transformation, and loading for businesses, integrating with key AWS services, allowing efficient data pipeline automation. It's valued for a user-friendly GUI, scalability, and cost-effectiveness, supporting PySpark for complex datasets and includes a robust data catalog, real-time backup capabilities, and code generation. Despite its strengths, improvements are needed in documentation, training, and broader programming language support. Users face challenges with its complex interface and integration with non-AWS products, driving demand for enhancements in its usability and performance.
What are AWS Glue's most important features?Businesses leverage AWS Glue in industries for ETL processes, data integration, and transformation. It is used to optimize data lakes or warehouses integration, enhancing data cataloging and real-time integration. Its serverless feature enables efficient data processing in sectors like finance and healthcare, where handling complex data-intensive tasks is crucial.
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.
We monitor all Cloud 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.