Denodo Reviews

My main use case for Denodo is that we have very decentralized data sources from different legacy applications, so this tool is very useful for us to connect all these legacy systems. This tool is very helpful for our data discovery and mapping. Getting real data from APIs and combining data from multiple systems were major challenges, which were solved by Denodo within a minimum replication cost.

A specific example of how Denodo helped me connect those legacy systems is that this tool is very easy to use and supports a multi-database infrastructure. We have a very large enterprise and we are blending data across the enterprise. What Denodo has helped us achieve is both federated and non-federated data with the same reusable data structure.

Regarding my main use case with Denodo, I also use it to build and send our data service to our partners and stakeholders and provide a real-time data experience to them. It is really easy to use, fast, and secure. Additionally, it is possible to combine many sources of data and integrate them with one tool.

The best features Denodo offers stand out to me as the ability to develop REST web services fast and easily, create and combine new views, integrate different sources of data, and connect with other tools seamlessly.

When I mention fast and easy creation of views and integration, I love the agile data provisioning and integration, where Denodo provides a comprehensive set of capabilities for implementing logical data integration, management, and delivery, which in turn enables agile data analytics and an informed decision-making process to be smooth. I also appreciate the performance optimization with AI, which improves performance optimization through the integration of artificial intelligence capabilities. Furthermore, I appreciate the unified security and governance, where it addresses the need for an organization to effectively manage security, data privacy, and data protection easily, offering a centralized platform that allows the application of governance policies and fine-grained security controls.

Another feature I would add about Denodo is that it also provides a single point of control where we can establish security controls over the entire infrastructure and gain visibility into all our data assets.

Denodo has positively impacted my organization as since we started using this tool, it has been very helpful because it is a huge advantage that we can connect to many different databases to provide data rapidly and accurately and also gain insights, which helps us to make data-driven decisions easily. It has proven to be a valuable environment for deploying data virtualization solutions, and its user community is active in finding and fixing issues more accurately.

Through data insights from Denodo, we have been able to improve our decision making, which helps to better communication between the stakeholders thanks to the real-time experience. It also saves a lot of time.

Denodo can be improved as it can be a little buggy, especially when dealing with huge data and is not great if you have very large volumes of data because it can be buggy.

To add more about the needed improvements for Denodo, I think the user interface should be improved to be more user-friendly and intuitive, especially for those new users who find the learning curve a bit steep.

I have seen a positive return on investment for one client who was paying too much for an existing legacy reporting platform that has not been updated in decades. For another client that did not have any traditional BI tools, Denodo is the perfect tool. It provides a positive experience for end users who can now run reports using multiple near real-time data sources, and a positive return on investment for those who can connect multiple data sources and make data-driven decisions easily.

The reason why we switched from Cisco Composite to Denodo is that we evaluated other data visualization platforms such as Cisco Composite and found that Composite had an even smaller community and less support than Denodo. Denodo is putting a lot of the revenue earned from licensing cost to grow the product, and we did not get that impression from Composite.

The advice I would give to others looking into using Denodo is that it is very well suited for large organizations with siloed datasets. Denodo thrives in these environments since large organizations can afford the licensing cost and are always tasked to mash up data from multiple environments through the organization. It helps to make data-driven decisions more easily and is very cost-effective, so I highly recommend it as a tool. I would rate this product a 9 out of 10.

I used Denodo for a few months early this year, from January to March. My main use case for Denodo during that period was visualizing data from Snowflake and other databases across multiple databases and doing various types of analytics on the data inserted in those databases. We used Denodo for getting the data across multiple databases and matching the data in between these databases to have a single entry point for our queries.

For example, we had a bunch of files arriving on Azure Data Lake Storage, and we needed to match when these files arrived to what we needed to do with those files that were stored in a Snowflake instance. So, we used Denodo to cross this data and select queries, and then apply the Azure function that we needed to do to these files that were arriving on our Azure storage.

Denodo offers a great query language, the VQL, which was very easy to understand for someone that only knows SQL. It was easy to work with, and it was easy to integrate various types of databases in general. The usability of the platform is very great. The federated queries were also a feature that I used a lot. The easy usability of Denodo helped my work and made things easier for productivity. We were able to ship code faster than if we needed to use another type of data visualization tool or even an ETL.

When we have multiple databases, the standard or common approach is just to have an ETL that matches the data, and we need to write this whole ETL. With Denodo, we can simplify this whole work to a few queries or setups in the databases and just make a few queries. This was actually easier, and it was faster to deliver a solution for a client instead of building a whole ETL pipeline or simply backfilling one database in another. Denodo simplifies your work and helps you ship code or ship solutions in a faster way. I really like the UI that Denodo has on the web app version. It was very simple and actually very beautiful to see. For a complicated program, it was very easy to understand how it works, even for someone who is just approaching the data engineering career or side of the programming language.

The desktop version of the Denodo app has a difficult UX to understand, touch, and set up. But they have fixed that on the web app version, which is nice. Overall, the platform works great with the current setup that they have. I didn't really get to know the quirks and the bad side of the platform, as I've only used it for three months. In my opinion, it's a great software, and it's not buggy at all. The interface is simple and easy to understand.

I've been working in my current field for eight years right now.

Denodo is stable.

The customer support for Denodo is great. They are very easy to work with, and all my questions and concerns were answered in a very short amount of time.

Positive

I didn't previously use a different solution before Denodo. When I saw Denodo for the first time, I thought it was great, but it was not my choosing to use Denodo; it was the standard platform for the company I was working at.

We use Microsoft Azure as the cloud provider for Denodo's private cloud deployment.

I can't share any metrics with you because I was just a developer. But my general impression is that yes, Denodo saves a lot of employees and development time. Because 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 didn't really manage the setup cost, licensing, and pricing for Denodo. But in my opinion, it's very expensive. For small companies, it's not a solution that most small companies can afford. But for big companies, the pricing seems fair. It would be nice to have a cheaper version of Denodo for small businesses.

My main advice is to read the documentation for Denodo. It's a very powerful solution, but it has a lot of quirks and a lot of things that can be done and should be done the right way to have better performance when using Denodo. The documentation is very clear and will help you 99% of the times. The review rating is 9.

Denodo is designed for a distributed data fabric. Instead of a centralized data lake, we are in a distributed data mesh. Whenever a team wants to publish some data product, they are publishing data through Denodo, and their data store might be different; it might be in Azure SQL, in an Azure Databricks data table, or in ADLS.

Whenever a user is looking for data, instead of connecting to each individual data source, they can only pull data through Denodo views, which is a virtualization layer. Role-based access control can be implemented. Not everybody can pull data; whoever is looking for data and whatever data they are looking for, that approval we can give, and based on that, they can pull.

For real-time analytics, we have an Azure Kafka endpoint. There are some use cases with the Azure Kafka endpoint; we have transferred data through that, and through Databricks, we have transformed the data and stored it in some persistent layer such as a Databricks data table or any other data store.

One of the best features of Denodo is that it's one unified layer. All programmers or software need to manage different endpoints through one Denodo endpoint. We have custom-developed a tool called Marketplace where we can see whatever data products are available. It is centralized through one portal, a one-stop shop.

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 distributed data mesh functionality allows teams to publish data products through Denodo, regardless of their data store type.

Role-based access control is another valuable feature, allowing selective data access based on approval. The Azure Kafka endpoint enables real-time analytics capabilities.

In terms of improvements for Denodo, regarding performance, in cases where there are multiple virtualizations—such as reading from one Denodo view that is virtualized, and from that view there's also virtualization, and another team is reading from that view—if multiple virtualizations happen with no caching in between, it becomes slow.

This occurs because it is cascading; whenever at the top level someone is reading data, that request is getting cascaded to the nth level, causing issues, especially in cases such as Power BI reports. We need to consider implementing some persistent layer in between.

The scaling process should improve because many things are getting automated. The scale-out part needs to be automated, though I am uncertain whether Denodo has already implemented that feature.

I have been working with Denodo since joining this organization, which is two and a half years. I believe the organization has been using Denodo for five years.

Denodo is scalable and is installed on a cluster, enabling scale-out capabilities. However, it cannot be scaled on the go. For huge data requests, it cannot scale automatically; admin action is required. The scaling process should improve as many things are becoming automated. The scale-out part needs to be automated, though I am uncertain whether Denodo has already implemented that feature.

I would rate Denodo's technical support an eight out of ten because whenever there is planned maintenance or if the Denodo server is down, we receive emails from the support team. If we raise a ticket, it can be resolved or addressed within a reasonable time frame, so support is good.

Positive

I am not certain what was used before Denodo as they had started using it before I joined. At that time, they might have had some legacy systems, and each team had their own ETL pipeline.

We are not using AWS, and a different team is responsible for onboarding or approving new software or licenses. Regarding advanced metadata management features, someone from the Denodo SME or Denodo admin team would be better positioned to comment.

We have used the caching mechanism. For huge data sizes, we are using Snowflake. Denodo has the feature to persist data in any data store. While Denodo doesn't typically persist data as it's a virtualization layer, we can persist data in Snowflake for large datasets.

Denodo can be deployed both on-premises and in the cloud. Initially, they started on-premises with the Denodo server, but have now migrated to the cloud. Denodo is the backbone for the BU I'm working for. If someone wants to share data or bring data, they need to go through Denodo, making it the backbone of this data mesh architecture.

I am not familiar with Denodo's pricing as that is handled by the budget or senior management team. We might be a partner of Denodo, but I'm not certain about this relationship. We are using Databricks Spark, not core Apache Spark.

I would rate the product overall an eight out of ten. I am satisfied, but there is always scope for improvement. If they fix scalability automation and virtualization problems, I would give them a higher rating.

I am switching from Denodo to other solutions. Currently, I work as a Data Engineer Team Lead at an Etex company, where I work with Oracle Data Integrator (ODI), Power BI, and sometimes Tableau. I use Oracle Data Integrator as my primary tool.

Denodo is part-time work with a Saudi company. My main position involves working as a team lead for ODI and Power BI. As a consultant, I determine whether Denodo is used in companies or if their customers are using it.

My Saudi company is Denodo partner in Egypt, and we work for clients in Saudi Arabia. I have been working with Denodo for the last three years.

I find the features related to data governance most valuable. The data catalog is particularly interesting, and it provides an overall point of view that is useful. From my experience as a data engineering team lead, I can build a data warehouse in just a minute from different sources without needing time for data transfer or any additional work.

Denodo can be improved by entering new markets. I am in Egypt now, and I think there are not enough companies dealing with Denodo. I faced issues when trying to find a new job using Denodo in Egypt, as it is very hard to find opportunities. Denodo should tap into new markets in the Middle East. Last year, I gave training for Saudi clients in Dubai, and even in Dubai, it needs time to find training centers or trainers to help spread Denodo practices.

I have been working with Denodo for the last three years.

I experienced a performance-related issue the last time I dealt with my client in Saudi Arabia, but I solved it by using some workarounds.

The issue I faced was related to data volume. My client has almost 100 million records, and the performance was impacted in a way that required optimization.

I did not always contact technical support from Denodo. I only contacted them when I took an exam as I am a certified Denodo consultant and developer. I faced a problem during the installation of Denodo on my laptop, and they helped me greatly to bypass this issue. This happened two years ago.

I solved the problem by myself.

The implementation is not complex at all for Denodo.

Denodo's security features are very aligned with my customer expectations. I can implement row-level security or column-level security, and I can hide columns from some departments. These security capabilities are very interesting.

I am satisfied with the performance for sure.

I did not deal with the pricing of Denodo as my company's financial requirements are managed by another team, so I do not know how much it costs.

Denodo's interoperability options make the integration process very easy.

I experienced something interesting when I integrated Denodo with SAP, and it was fantastic. Data governance is something very interesting as Denodo helped clients get what they need. I did not use the new AI features, as I expect no additional features from them related to generative AI. I did not deal with vector databases and do not have experience with them. I would generally recommend Denodo to others. They need to promote the product in the Middle East, but I am recommending Denodo to different companies. I am not sure how customers are dealing with Denodo from the AWS Marketplace or directly. I give this review a rating of eight out of ten.

My main use case for Denodo is jobs which I require for test data, so that is one place where Denodo has come in. I think we have to write SQL queries, and there are cases where there are AWS Redshift databases. There is a difference in query results that we have to validate between legacy and modern systems, which is one of the use cases. Then when we test using Rest Assured or using Postman, there is a layer of Denodo that comes into play.

I can tell you about a specific example where Denodo made a difference in one of my test data or validation projects. We had a case in one of the projects where we had a large number of APIs that were sequentially connected with each other. What exactly was happening there was that there was a UI developed, then there was this API, and several AWS services which we were working with together. Denodo came into the picture because there were some masking and security-related customer emails on local QA environments. So there was a use case of real data where we could not really scrub the database. Denodo had an implementation there.

The best features Denodo offers in my experience include a very solid compatibility with AWS and AWS Athena. Denodo also works with EC2 auto-scaling groups, so the scalability aspects are excellent. Denodo is installable via AWS Marketplace directly, and that installation part is seamless.

Denodo has positively impacted my organization, and I have noticed changes since its implementation. The performance of our application has increased significantly. Earlier, we used to have several outages or slowness that users reported, but now those things do not happen.

I can share specific outcomes or metrics. Latency was one of the metrics being tracked, and we were at double nines sort of accuracy in latency. The latency slowed down by a factor of about ten altogether, which was a key metric observed after Denodo was implemented.

Denodo can be improved in some areas. We faced some issues with respect to Java client dependencies and had significant hassle with version management. Improving version management is something Denodo can work on.

I have been using Denodo for close to two years, on and off in two different organizations.

Denodo is totally stable in my experience.

The scalability of Denodo specifically helped my team or projects in situations where it made a big difference. We had one application deployed on a multi-continent system where several different countries used the application at the same time. The application was taking performance hits and slowing down at times. Denodo's scalability comes into play specifically when there is data transfer.

Denodo's scalability is good. It scales well, and I scaled it across two continents and four countries with very few issues.

I have not interacted with customer support.

The company did purchase Denodo through the AWS Marketplace, although not me personally.

My experience with pricing, setup cost, and licensing is that licenses were bought at an aggregate level from a vertical, which had significant costs. However, I am not sure about the specific pricing and setup cost, as these were centrally handled.

I have seen a return on investment, which showed up in improved customer satisfaction scores. It was not exactly about money or time saving, but the customer scores did improve.

I think Denodo was the top choice, and my organization did not evaluate other options before choosing it.

On a scale of one to ten, I would rate Denodo a seven. I gave it a seven because it was not held back or anything. We had a very limited use case as QEs, and we used it as a supporting layer or an intermediate layer. It was more useful towards teams that had dedicated performance reduction goals that we did not have, so it was all good to me.

My advice for others looking into using Denodo is that if you have multi-country applications, latency, and slowness and are looking to optimize queries for better performance at a backend layer, especially with many APIs or microservices, Denodo is the solution to choose.

I have no additional thoughts about Denodo before we wrap up as I think I have shared everything. I would rate Denodo a seven out of ten.

I use Denodo to create a virtualized data environment rather than a physical one. This is helpful when enterprise data is spread across different data sources, such as cloud data warehouses and data lakes, and is used for developing AI and ML strategies. It creates a unified virtualized environment so the algorithms do not need to connect to multiple data sources individually.

Denodo creates a virtualized environment that provides one unified destination for all data sources so that AI and ML algorithms can connect to that virtualized destination without needing to establish connections with multiple data sources.

The most valuable feature in Denodo is data virtualization. This feature focuses on creating a virtualized data environment that allows for simpler connections between data sources and systems. It significantly eases the process of developing AI and ML strategies by centralizing access to various data sources and allowing algorithms to efficiently connect to and utilize data.

Denodo's complexity level is high since it connects multiple sources, sometimes creating glitches in the production environment. The stability of the features can be improved. The system has dependencies on other environments, like JVM, which can affect its performance.

I have been using Denodo for about two to three years.

Denodo shows stability concerns due to its dependency on external environments, such as JVM. If JVM does not function properly, it may cause Denodo to fail to connect to different sources.

I would rate Denodo's scalability as six to seven. Its complexity in configuring and the requirement to install different connectors for different sources affects its scalability.

Denodo's technical support is rated as seven. Although they are proactive in conducting webinars and connecting with customers, they are perceived as less proactive compared to some other vendors.

Neutral

Configuring Denodo involves setting up a Java environment and installing different connectors for various data sources. This can take one or two weeks depending on the number of sources.

Denodo's pricing is not affordable for small companies and is more suitable for medium to large enterprises. On a scale of one to ten, where ten is most expensive, it is rated around three to four in terms of cost.

For new users evaluating Denodo, it is crucial to determine whether you truly need a virtualized environment. If you do not have numerous data sources, Denodo might not be necessary. However, if you do, Denodo makes sense. 

I rate the overall solution as eight out of ten.

I am a consultant and a freelance data engineer with experience in Denodo. I work as a data warehouse and BI consultant, owner, and managing partner. I assist my clients, primarily in the public sector, including government organizations, with IT solutions using Denodo as part of their infrastructure.

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 acts like a database query engine without a specific database storage technology. It is a very intelligent query engine, providing an abstractness to information at a meta and meta two-level. 

Additionally, Denodo's capabilities offer a strong and intuitive solution for data access.

Denodo is like a Swiss army knife, but it's challenging to deploy it as a clear solution because it presents itself as a tool that can do anything. Denodo needs better communication on how the product can be deployed for specific solutions, and there are price issues, as it's considered expensive. It requires improving the story of how it can solve specific problems.

I have two years of experience working with Denodo.

The stability of Denodo is high. I would rate it nine out of ten because it is very reliable, always performing as expected.

I have not worked with large deployments of Denodo, particularly in a clustered environment. While the solution scales well on a single machine, I have doubts about its scalability when deployed as part of a Java component cluster. Therefore, I rate its scalability at seven or eight.

Denodo's customer support team is very competent and responsive. They try to simulate problems and address issues promptly, although most problems relate to network or authorization protocols, not the product itself.

For me, the initial setup was not a problem due to my extensive experience with UNIX and databases. However, customers have found multilingual support somewhat lacking, and documentation has not always kept pace with rapid product changes.

Denodo is considered pricey, limiting its use to large enterprises or government organizations that can afford its comprehensive setup.

While I rate Denodo nine out of ten, I recommend considering the specific use case before adopting it. Denodo is a tool and should be part of a well-thought-out solution. Don't rely on marketing claims that say Denodo can handle everything. Solutions should be designed to solve specific business problems.

Denodo is used for data virtualization and not for data visualization. We are in the initial phase of using Denodo, performing a proof of concept (POC) to understand its features. It is used for connecting to various data sources and combining data without storing it.

Denodo provides flexibility in connecting to multiple data sources. It enhances data performance by using data caching. It allows for combining heterogeneous data formats and provides a mechanism for querying in natural language.

The data catalog feature is valuable as it helps define data structures without storing data. Denodo's ability to connect to multiple data sources and perform extract-transform-load (ETL) operations on the fly is noteworthy. It supports API usage to call and present data in JSON or Tableau format without visualization capabilities.

As we are still in the initial phase, it's difficult to identify weaknesses. However, ensuring data caching is up to date is critical. While AI and ML integration is present, understanding its implementation better could be beneficial.

I have started using Denodo since last month.

Denodo provides high reliability, with features like vertical scaling, horizontal scaling, and failover nodes.

Denodo provides high availability and flexibility in infrastructure and architecture management.

I have not yet needed to raise a ticket with Denodo's technical support as most questions have been answered through the community resources. I am in touch with some Denodo technical team members who explain the product features.

Positive

I used Qlik Sense for over six to seven years. 95% of my queries were answered through Qlik's community, and their support was prompt. We were Qlik customers, not partners.

The installation process is simple, whether on Windows or Linux servers. The setup is easy and provides flexibility from an infrastructure and architecture point of view.

End users of Denodo will mostly be non-technical, as they will query the system in plain English for data insights.

I'd rate the solution nine out of ten.

My main use cases for Denodo involve implementing APIs to connect different data sources with new software to improve the process in Ecopetrol.

Denodo's best features are that it is very user-friendly and easy to use. It is flexible, and the data catalog is very useful.

The data cataloging has helped me in data discovery because this feature is very useful. All the people of the company can find different data for different projects. We created a data catalog for the company and to publish the API, and the different projects can use the APIs and reuse them.

To make it easier to use or a better tool, the architecture and internal design of the folders for organizing the structure of the different data could be more structured. Denodo does not have a guide for easily structuring the data.

In the last 12 months, I am not still working with Denodo. This year I have not, but last December, I was using it.

Denodo is stable and good. I do not have crashes normally.

My thoughts on scalability are that it is good because I can use different setups or configurations.

I do not use the technical support, so I cannot rate the customer service or technical support.

I have not evaluated other data integration tools before because Denodo was the tool in the project and I do not see other tools.

The initial setup of Denodo was medium complex.

I do not know the pricing for Denodo because I only design and develop.

The security was good for us.

I do not have anything else on my mind as far as valuable features.

I do not know if the dynamic query optimization helped us improve performance or analytical queries as I am not familiar with dynamic query optimization.

My overall rating for this solution is 9.

We are currently using it in our company, and it's our data virtualization tool. We fall under the federated analytical model. Basically, we have data that moves into our warehouse, and from the warehouse, when we want to build our reports, we use it. So, we are mainly using it for reporting purposes at this point. Instead of building aggregated views in our warehouse, we put that on the Denodo layer.

We aggregate the data in our Denodo layer. Because Denodo is a virtualization tool, we try not to cache the data, but we've cached it whenever needed. Our dashboards usually run once a day or twice a day. So, we refresh the data once or twice a day. Sometimes, we also refresh every hour, but mostly, we refresh once or twice a day. For that, we don't need the data materialized in a view. We don't need the data to be there. We just create these views on Denodo. We have Power BI and Qlik Sense, and we just use those tools to pull the data from Denodo.

There are other uses as well that we are thinking of as a company. We have business users who do want to look at the backend of what's going on. They may just want to run something like a quick analysis. For example, for a question, they just want to go take a look at the actual data. For that purpose, we can give these analysts access, and they can go in and take a look at that. Eventually, we want to go to a place where we want to enable self-service analytics for our business users. We are thinking that Denodo could help us in that direction. I know different companies use Denodo for different purposes, but we are using it on the IT side. Currently, we are using it mainly for reporting purposes, but we could also move towards self-service and make it available to our business users as well. That's for the future. We haven't done that yet. For now, we are only doing it at the BI layer.

One thing that we have noticed is that when you have a BI tool, you end up building a lot of the logic in the BI tool, but as a company, every company wants to be tool agnostic because today, you could be in the Qlik Sense, and tomorrow, you may decide to go with Tableau or something else that is there. If you have put a lot of logic within the tool, transitioning or moving away from one BI tool to another tool becomes a very intensive process. By keeping the logic in Denodo, you can move to any tool. That's what we have done at this point because we used to have Cognos in my company before. When we did the migration from Cognos to Power BI, it was quite intensive for us because a lot of the logic was sitting in SQL queries within Cognos. To move to Power BI, we had to do a lot of backward thinking. These reports were built more than 5 years ago, or even 10 years ago, and the people who built them were no longer with the company. The logic was pretty much gone. We didn't have good documentation, but now, after we have put the code in Denodo, we have visibility. Any developer, not a business analyst, can come and take a look at that code and discern how the data is moving from the warehouse to Denodo. All that Power BI or Qlik Sense is doing is just pulling the data from that view. We can do averages and other calculations in the tool, but at least our aggregation and the logic are in the Denodo layer, and then going forward, we can take it to any tool.

Last year, they moved from version 7.0 to 8.0, and version 8.0 gives a lot of flexibility.

I would like it if we could pull the data model or export the data model because Denodo has, based on how you build, something called associations. The data model gets very confusing when you go look at it. It depends on how you define it, but it's really huge. I wish there was a way to export it into Visio. It could be that they already have a way to do it, and I don't know, but it would be much easier for the architects and even for the developers to look at it than scrunching it into the screen and expanding every small portion of it. If there was an easy way to export the Denodo model into another modeling tool and view it, it would be great.

We are also trying to use Denodo as a cataloging tool so that we can put proper definitions, and once they are made available to our business users, it becomes easy. Using the Denodo layer, we can write queries to pull data. There is a virtualization layer. So, we can interact with it just like any other database. If there was a way to write a query and make my query public to other users so that they don't have to come in and write their queries, it would be great. There should be reusability of something that I did. For example, if I'm working in the healthcare industry and I want to get a view of the patient count for the whole year, I should be able to write a query and make it public so that whoever wants to use it can use that query instead of creating the same query again.

I have been working with this solution for a little over three years.

It has been pretty stable. We've had some minor issues here and there, but we do have an admin who is assigned to this. We have a full-time paid Denodo admin. If there is a problem, he is very fast at getting onto the problem. He connects with Denodo and then comes back with solutions. Overall, we've had minor things here and there. Sometimes, we have to use certain Java functions to figure it out. There is also a learning curve for some people because not everybody knows Java coding.

We recently upgraded to Denodo 8.0. We pushed the upgrade for a very long time because my team is the biggest consumer of Denodo. So, we had to look at our timelines to do it, but it was very smooth. Denodo helped us really well in the upgrade, and my team and our admins were also on top of everything. The whole Denodo 7.0 to 8.0 upgrade went smoothly. It went so smoothly that I just couldn’t believe it.

So far, it has been good. We have between 50 to 100 users. It is used on a daily basis.

I'm not super familiar with that mainly because our admin is the one who takes care of it, but he hasn't complained. So, their support should be okay, but it's hard to know how good or bad their support is because we have a full-time admin.

I haven't used any other solution. I have used virtual data lakes. On Hadoop, I have used that. One thing that I felt is that there is a learning curve for Denodo. It's not something that people just start using. They can learn it, but it's going to take some time for them to get to know it. For example, if you know SQL, Oracle, or Teradata, the structure is pretty much the same, but I cannot have a developer come in and start working on Denodo from next week. It's not possible. They need some time.

When I came to the company, the initial setup was already done. It was already there, but from what I have heard, Denodo has been very helpful with the initial setup. We did buy a package so that we get the initial help for setting up everything.

I am not super familiar with the pricing, but so far, it seems good. We have been happy. We haven't seen any problems.

The only time we had to pay extra was during the upgrade. We didn't upgrade at the time they told us to upgrade, and we had to pay extra to keep the service. They had stopped the support for the older version and moved to the newer version. It was not their fault. It was our fault because we didn't get on board quickly.

There is a learning curve, and you would need at least two to three weeks. You can make it very complex, and you can make it very simple. I know different people do it in different ways. Ours was a little bit of a structured process, which could also be the reason why it takes some time for people. We don't just approve everything through Denodo. We have a review committee, and the review committee decides and approves or denies a new table or a new view. We have a review process. That's one of the things that has helped in keeping Denodo's environment clean.

I would rate it a 7 out of 10. The reason is that in our company, we haven't explored everything that Denodo can offer. The tool is good, but we've only scratched the surface, and it may have additional functionalities that we haven't used. The more we use Denodo, the more we'll like it.