Denodo Reviews

My primary use case is for data virtualization. I'm working in the pharma domain, so there are large amounts of data coming in from different sources, which I aggregate into Azure SQL, some other web services, and SAP applications like CRM, POS, and others. Denodo acts as a virtualization layer, where we are collecting and creating views for analytical purposes. So we use Denodo to integrate and transform. It is deployed on-premises. 

The most valuable feature is the performance. Denodo is very useful, especially in this huge pharma environment. I've found that older SAP solutions were very tightly coupled to each other, which resulted in data restrictions. Getting data from different sources was tough and tedious. Compared to these old solutions, Denodo is very easy to work with for the analytical team. Now that we've implemented this virtualization layer, we are capable of getting the data very smoothly. We implemented a very small unit, but the performance and integration have been very good. 

Denodo's training documentation could be improved by providing more material. From an administrative standpoint, I've found that only Denodo websites provide the usual tutorials. It may be because it's a bit of a restricted tool, but it results in trouble with learning. Normally, I can find help and solutions from other sources, but I haven't been able to find any for Denodo. Other that, it's fine and it performs well. I only have six months of experience, so I can't accurately suggest improvements. 

I have been using Denodo for almost six months. 

Currently, we haven't found any discrepancies or problems with stability. We are a team of 25 using Denodo simultaneously, but we're still in a development and testing environment. Once it's in production, we'll be able to tell if there's any kind of a bottleneck. 

Our Denodo administrative team created a pipeline from one environment to another environment and we haven't had any trouble yet. The production deployment is going to happen soon, so within a month or so we'll have a better understanding of the production data, streaming data, and all that. 

Technical support is fine. I will say that my team and I are interested in pursuing a Denodo certification. I was looking for a way to take the Denodo Administrative Certification 8.0, but I'm still waiting on that. Developers are restricted right now because we need to pay for each and every topic in Denodo. 

I have worked with Azure Data Factory. With Data Factory, you need a staging solution, a physical data platform for storage. Denodo doesn't need this, since it has a cache mechanism. 

I have also previously worked with TIBCO, but that was more service integration than data integration. 

The initial setup was easy. Also, connecting Denodo to Power BI was a smooth process. It was simple to connect it with a Denodo ODBC connector. So installation and connecting with other tools were both very easy. 

For deployment and maintenance, we are a team of two developers. It took around eight months to develop the unified views. 

I implemented through an in-house team. 

I rate this solution a seven out of ten. I work in an advanced analytical area where it helps to reduce bottlenecks, extract from different application sources, improves performance, and gets the desired data, which is what those endpoint people need. 

If you have a vast data fabric or data mesh architectural framework, I definitely suggest implementing this kind of a virtualization layer. I recommend Denodo because it has been very easy, compared to other integration platforms. 

We have around 100 people using this solution in my company. The solution is deployed on cloud and on-premises.

The most valuable features are query optimization and the single language independence from the sources we're using to catch data.

I would like to see a proper way to avoid killing the sourcing systems. There is some parameterization in this case if you push down the query to some systems, but I think there are still issues with giving this tool to end users because they could write queries that could cause a lot of issues in the operation systems.

I have worked with this solution for more than two years.

It's quite stable.

It's scalable.

I would rate technical support as four out of five.

We compared this solution with TIBCO. We chose to go with Denodo because we had some daughter companies that previously used TIBCO and gave us some feedback about it.

Setup is simple on the cloud. The on-premises setup could be more complex depending on the security firewalls.

I would rate this solution as nine out of ten.

I think the business metadata should be available to help people understand what kind of data is being connected. This makes it difficult for end users to use Denodo.

I would recommend this solution to those who are interested in it.

Our ETL team was preparing the data warehouse, and we used Denodo as an intermediate solution.

It can support a number of data sources, and it can pull flat files, from cloud-based databases or from those on-premises. Denodo can pull from any data source and interface with the view. Then, we can publish the view. 

Though it's not a full ETL solution, teams downstream can utilize it, prepare it, and consume it in a secure way in multiple formats.

User-specific security at the column and row levels needs to be improved. Instead of applying security at every individual level, it would be better if it were at the group or tier level. It will save a lot of time.

Denodo could also improve the UI, data governance, and cataloging.

I've worked with Denodo for two years. It is on the database cloud, and it is a Linux based OSv.

We are satisfied with the stability now. We had some connectivity and driver-related issues earlier, but Denodo's technical support team helped us resolve them.

The architecture can support horizontal and vertical scalability. You can expand your servers if required, or you can expand vertically and also increase the size of the system.

In my company, in India there are 200 to 300 users. We have expanded to the US and plan to increase usage.

Denodo's technical support team helped us a lot. They resolved all our issues, such as connectivity and driver issues, because they have experts.

We bought both TIBCO Data Virtualization and Denodo. TIBCO is a strong product and was good, but the cost was an issue. The cost was the main factor and resourcing and support also came into the picture. TIBCO did not have much of a global presence. Given Denodo's licensing model, support, and market value, they opted to go with it.

Initially, we had a lot of trouble, but later on, our DevOps team prepared a script. Then, everything went well. Now, it takes half an hour to set up a new environment.

We have two people who handle the deployment and maintenance.

We handled the deployment in-house.

Cost wise, on a scale from one to five, with one being the cheapest and five being the most expensive, Denodo would be at three. We get all the features in a bundle.

They initially evaluated TIBCO Data Virtualization. However, Denodo was much more flexible and worked cost wise as well.

Deonodo is Virtualization for Logical Data Warehouse but is not a full ETL solution. You can use it if your dataset doesn't require that much ETL cleansing. On top of that, if you want to quickly show your data and use your data for  analytical purposes, then this is the best tool. We can connect to data sources on the go and can perform data privacy, data governance, etc. This is the best tool compared to other similar tools available on market. On a scale from one to ten, I would rate it at eight.

In the past, transforming data from databases to other tools was a tedious and time-consuming process. Denodo eliminates that hassle, saving me time and money.

So, Denodo improves data integration processes. It reduced the time to go live and required fewer human resources to make data accessible across the company.

Moreover, it supports our reporting needs. I use Bar BI for reporting, and Denodo's ability to connect directly to native data sources without complex configurations is a great feature.

I like the integrated views. They're incredibly useful, along with the overall integration capabilities.

The logical data warehouse functionality is fantastic. It truly stands out.

The ClearOptimizer and Virtual Cache are great features. They work together seamlessly to optimize performance.

I'm waiting for them to introduce the generative AI capabilities they mentioned would be available by the end of the year. That would be a game-changer.

Moreover, I would like to see the ability to utilize vector databases. 

For some internal strategies, I need to publish data into vector databases. Denodo currently integrates with ChatGPT, but the ability to manage and utilize them directly within Denodo would be a significant improvement.

I have been working with it for a year now. 

We never had performance or scalability challenges with Denodo.

The customer service and support are fantastic. 

I used SSIS as an ETL tool and some IBM staging tools, but not extensively.

I used SSIS at my previous company and then switched to Denodo here.

The time to market is significantly faster with Denodo, both for deployment and publishing updates. Additionally, the web service capabilities are fantastic. We can deploy any web service in just minutes without complex development or security concerns.

If you need immediate access to data (within 3-5 days), Denodo is a great solution. However, for complex data silos, I recommend trying a demo for a week or two before making a decision.

Overall, I would rate the solution an eight out of ten.

We use Denodo to fetch ad hoc reports. The users can join tables or views and fetch the reports on their own. It is not a soft controlled environment or an OCC controlled environment, so they can do whatever they need. The have some room to play.

Data mining is one of the valuable features. We're able to connect all of the data sources with the installed driver, so that is a good advantage in Denodo. Being able to join the tables and view them is also valuable.

Monitoring event logs can be improved. In the older version, there was a monitoring schedule to get event reports and properly audit the reports. In the newer version, it is not there, and we have to manually configure data and audit events.

Denodo could create a UI for us to monitor the events. They could also provide a good training environment or basic training on how to create a view. At present, we have been creating our own material for training. It would be better if Denodo could provide that training material for beginners.

I've been using Denodo for about six years.

It is scalable, and we have 500 users.

I would give Denodo's technical support a ten out of ten.

Positive

The initial setup is very simple. Two people are sufficient for deployment and maintenance.

I installed it myself.

The pricing is pretty good, and I would rate it at four out of five.

Denodo is an easy tool that can be used for data mining. You can connect to all of the data sources. You can see the views easily.

A beginner may find installation complex as he will have to configure the scheduler, the VDP client, and the audit as well. However, it will be fine for an experienced person.

Overall, on a scale from one to ten, I would give Denodo an eight.

I work for a company that provides financial solutions to banks and advisors. We need to send data everyday to different third parties in different file formats, like pipe delimited, comma separated, fixed width, xml, etc. Previously, we used to generate those files with the data using PL/SQL. After looking at the performance issues and the complexity, we started using Denodo.

We run scheduler jobs in Denodo, and the job will in turn run the VQLs. VQLs will gather the data based on the business rules and business logic. Finally, it will spool the data in a predefined file format, and then the file will be delivered to the respective recipient. Basically, we generate interfaces using Denodo.

Caching was very valuable to us.

In PL/SQL, first you need to gather all the data and then start writing the file, but in Denodo you fetch the data and write the data simultaneously. So, for example, if you have 1 million or 2 million records, you don't have to wait to fetch all of the 2 million; you can keep on fetching and writing in the file simultaneously.

Tasks such as conversion of a date format or conversion of a number format that can be done in a very easy way in different languages, like SQL or Oracle, are not so easy to do in Denodo.

For example, if you want to convert a date from one format to another, in Oracle it's pretty easy; in Denodo, however, it requires so many lines of code. Simple things that can be done very quickly in other database languages require more lines of code in Denodo.

The scheduler UI in 8.0 is not as good as that in 7.0. We have thousands of jobs, and if you search one job, get it, and click on it, when you come back, your search will be gone. You have to do your search all over again. The 7.0 UI was much better.

We have been using Denodo from the last quarter of 2018.

Right now, it's deployed on-premises, but in the next few months, we are planning to move it to the cloud.

It is scalable.

We have three administrators and about 20 to 25 developers working on this tool.

We have biweekly meetings with Denodo staff. Apart from that, whenever we have any issues or concerns, we just raise the ticket on the Denodo portal, and we get a response. The technical support is good.

The initial setup was okay for us and was not complicated. We created a couple of virtual machines; we got a 4-core license. We installed two VMs, and one was always active. The second one was always down. Whenever we needed the second one, we brought it up. Otherwise, we mainly worked on one VM.

Once the VMs and all the machines and infrastructure were ready, the installation and setting up of all the configurations took two to three days maximum to complete.

For maintenance, we have three persons, two on-site in the US and one offshore.

We deployed Denodo ourselves.

Before Denodo, our interfaces were running for six to seven hours to generate a file. After writing the same thing in Denodo, now those interfaces are generated in 25 to 30 minutes. So for us, we came down from seven hours to 30 minutes, and that is our ROI.

For us, the cost has been okay. Also, there are no additional costs; it's just the standard licensing fee.

First, understand your use case properly, and then analyze the tool and see whether or not the tool is going to perfectly fit your use case. Denodo is mainly for data virtualization, though it has the functionality to create files and write data in the files. However, given my four years of experience that is not the best use case for Denodo. For data virtualization and fetching data from multiple systems and data sources though, Denodo is a good tool.

I rate Denodo at six on a scale from one to ten.

Denodo is a tool used for data virtualization. Our company provides services to our customers. One of our customers is on the Denodo platform.

Denodo is lightweight in terms of how it leads you to combine your discrete data systems in one spot. You are able to logically define and create your desired data set without actually getting your data shifted from the data system like any trivial ETL system does. It will not perform any data movement.

The solution provides ease for accessing data in various ways, including on-demand APIs. Uploading your data on an API will take less than an hour.

Denodo provides a good experience in terms of data visualization. The data on demand is the best feature. I also enjoy the go-to feature for data fabrication, or data mass structure, where data democratization is being sent data for all people at that time.

There are a few cosmetic changes that would make Denodo better, including offering holistic governance. It would be beneficial if you could see what inquiries are going around Denodo on the remote system, including who has logged in and which one is using which part of the deviant spaces. 

Denodo has provided several modules with their scheduler that also have room for improvement. 

When thinking about future releases, Denodo should consider their platform availability because our administrator has seen some challenges in this regard. It requires some optimization on the developer side as well. 

Denodo would benefit from having a more user-friendly view. It would be good if the solution provided a much-needed cellular platform.

I have been using Denodo for five years.

The stability of Denodo is okay. You will encounter some load optimization and performance tuning, so you do need some technicality around your data pack. 

The scalability is there. With AWS, there is elastic computing that manages scalability.

We currently have over 200 people working on Denodo. This includes our customer's manufacturing organization as well as people from business intelligence and analytics. They consume data directly from Denodo.

Customer service and support with Denodo is quite good. Our concerns are resolved and addressed on time. Overall, I would rate Denodo's technical support a four out of five.

Positive

The initial setup of Denodo is straightforward. The time it takes to deploy depends on each scenario. If you are looking for an inspired level of adoption, that will require time to model the data. However, if you are looking to use Denodo on a more simplified basis, deployment will not take longer than a couple of weeks.

Being an architect, I would rate the ease of setup a four and a half out of five.

Denodo typically provides a positive ROI within six months.

Licenses are available for the solution manager or for one of the components. It is a fixed price license for those that connect. The cost for Denodo is in line with other similar products.

The first comment I have for anyone considering implementing Denodo into their organization would be to ensure they understand that they should not expect ETL from Denodo. ETL is an old concept of data integration, while Denodo is the latest version. 

With Denodo, there is no need to further your ETL workflows. The workflows will be created in parallel, and you will realize how the Denodo implementation is setting it up to replace your ETL flow. You do not need to smooth or attach anything to what is currently running. By working in parallel with what the Denodo system is using, you will be able to copy across your users on Denodo and realize virtualization over your ETL. 

Overall, I would rate Denodo an eight out of ten.

We use the solution for data virtualization to publish the data as a product. We have different teams who have their own database. If a team needs any data, they get it from Denodo.

It is easy to virtualize data using the solution. If required, we can also use the solution for caching.

The solution is slow when there are many virtualization layers. The solution is also slow when we connect the on-premise solution with the one on the cloud through a network gateway.

I have been using the solution for two and a half years.

The product is stable.

More than 100 people in the organization are using the solution.

As a developer, I can easily set up the solution on my local Kubernetes. Local configuration is pretty easy.

A lot of virtualization leads to data latency. We can do caching on the intermediate layer. We can also leverage Databricks if we have any complex transformation.

I have a local Docker container. I can easily integrate my local container through Git repo and clone it in our depth server. Denodo is the only tool I know for data virtualization. I will recommend the solution to others. Overall, I rate the product a ten out of ten.