Denodo Reviews

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.

Currently, we are using it on Azure. We have around four VMs with Denodo divided into development, quality, and production environments. We have various configurations. I don't really work developing the queries on Denodo, it's more on the administration side. I have managed the scalability, the configurations, and providing the environment.

Currently, we use Denodo mostly to query data from SAP. We have a very old SAP inside of Schaeffler that doesn't have encryption. To retrieve this data from other people, to use the same data, we use Denodo to make this encryption. Then we have a few databases, and we can create base views based on the SAP tables. 

In some use cases, they also create web services based on these tables as well. They use it a bit as an ETL tool. They use for data scouting. For example, we have one tool that was developed inside of Schaeffler called Discovery, where we used Denodo to get the metadata from basically all the different systems that we have.

It's been useful to have the same language to query manager-friendly databases. That would be the main benefit. The second one is that we can create web services without any programming based on the base use that we create on Denodo. 

Getting queries is great. They are really good. You can basically write SQL statements, and it can convert to MDX queries or to MongoDB queries, or any kind of data source. We have many different data sources. You just use the requisite language, which translates to all the underlying data sources. That's the best thing that we have on Denodo.

In general, it's good for us to make tests so we can scout the data. We can make POCs easily. 

It's not really scalable. We have a couple of problems with a high demand for the servers. It also doesn't have very good integration with Git, so it's not possible to work with branches with the developers. When it goes to production, then we cannot use it anymore.

The git configuration really should be improved. It would help a lot. Then the developers could have different values of the same project and use, for example, GitFlow for the projects. That would be amazing. If they had it, the scalability would be very good. And we can actually have one external metadata database for starting the Denodo configuration. However, it's very slow. 

If it were possible to work around Kubernetes, for example, it would help. They have some implementations. However, it doesn't really work as expected.

The solution is expensive as you are charged by the CPU. 

I've been using the solution for three years. 

For production the stability is okay since we don't have a lot of things going on. In production, we have a couple of years of use cases. Of course, there is a high demand for CPU and memory. However, in development, we have a lot of issues based on the problems we've had with the Git integration. There are a lot of conflicts, there are a lot of problems.  

If you have just the applications pointing to Denodo and running the specific query, it's okay.

The solution does not scale well at this time. 

We have a lot of users. They don't do the deployments. However, they do development in the development environment, of course. I would say we probably have 100 users.

I don't like the support. They always blame the customer. For example, sometimes we have some bugs on Denodo and open a ticket. They ask you to run thousands of tests to ensure that it's not a bug, however, in the end, it is a bug, and we knew since the beginning. Sometimes it takes a week for them to say, "Yeah, okay, it's really a bug." 

Then, God knows when they will give an update as they have one voting system at the service desk. Other customers need to vote on the same bug or the same feature that you requested, and then it will go in the next release. 

It's very hard, for example, to have a call with them. It's very hard to get support when it's a problem with the tool. They always say that the customer doesn't know how to use the tool and it's not so nice.

I was in touch with a company called Starburst and CData. They seem to do nearly the same stuff. We just had to try the tool, to install and try to run the same things on Denodo. I didn't really have time for that, so I cannot say a lot. However, it could be an alternative.

It's very easy to set up the product. We have the solution manager on Denodo, so you can basically create a revision. Suppose you have the database from one environment, for example, from development. In that case, it will generate basically a backup, and it will deploy this backup in the other servers that you want.

We have three people that handle the implementation and deployment. It's me and two students in my team who are learning how to do this stuff. We basically have three DevOps engineers who are in charge of that.

The deployment of Denodo is very quick. It takes less than a minute.

In terms of maintenance, usually, we don't have many problems. Sometimes we face issues with credentials, however, the procedure that we need to establish is not yet well-defined. That said, usually, in production, we hardly ever have problems.

I don't have details of how much it costs, however, it's expensive. 

You pay per CPU. If I have 10 CPUs or 12 CPUs, it increases the price.

We're a customer and end-user.

We're using the latest version.

We have a contract until the end of 2023. Then, maybe after that, we won't want to keep this technology. That said, we don't have any replacements so far. We have to run some POCs and tests and plan a migration since we have around 46 use cases on top of Denodo. It needs to be planned if we decide to switch.

A potential new user should run a lot of tests before they pay a license. For example, try the support and see if the relationship works. There are some customers that are very happy. We have not been as lucky. Some are very happy, some of them they are not so happy. It depends on what your usage will be.

I'd rate the solution seven out of ten.

We use Denodo to improve data governance and self-service BI.

We had several data environments, one data lake, one data warehouse, and another instance of data in another silo, and we needed to deliver this data to our end users in an organized manner.

It was very, powerful because we could deliver this data in a short time and with some data governance, because you deliver it through a data catalog and you have the data lineage, and you can put there the role level security, column level security, and it was very helpful for us, and the end-user was very happy to have it.

The most valuable aspects of this solution are the short time frame in which you can deliver and connect.

I don't have a single feature because I believe the ability to connect disparate data sources is extremely useful. 

You can create a layer over these various data sources and deliver the data to the end user as a single data source. This, I believe, is the most powerful feature in Denodo, because it is data virtualization.

Consuming metadata from pipelines is something that would most likely be interesting. If we could integrate it, for example, with some ODI or some Data Factory, because if you have this, you might be able to take advantage of the work that the tech engineer has already done, and you might be able to turn Denodo into a more powerful solution because it can be used for more than just data virtualization.

The feature that you have to connect on LDAP needs improvement.

I am not sure if it's on Denodo's side, but sometimes it is very difficult to connect on LDAP, and you can take advantage of this by using the roles that have already been created there.

I have no complaints about Denodo's features, except perhaps the price.

I have been using Denodo for approximately one and a half years.

I no longer use it, but when I did, I started with version 7 and by the end of the semester, I was using version 8.

It was deployed both on-premises and on the Cloud.

In one company, I use on-premise, and when I worked at a consulting firm, I assisted in deploying a cloud environment for our clients.

Denodo is a stable solution.

Version 8 is much more stable than version 7.

Denodo is scalable.

We had approximately 1,000 users.

I no longer work for the same company. However, as a consultant, I always try to bring it to my manager in order to sell it to our clients, because as someone who works with data governance, I believe Denodo is a powerful tool for reducing the time it takes to implement data governance while also providing organized self-service BI.

The technical support is great.

I would rate them a five out of five.

Previously, we used Dremio, which was the only solution that allowed us to use it for free due to its open-source nature. We tried Dremio, and during the PoC, we didn't try any other tool, but we could see some presentations about Data Virtuality, which is a German company if I'm not mistaken.

It was a pleasant surprise to discover how simple it is to set up this environment.

We have a development team of five to maintain this solution.

When doing the PoC, we did use the consultant.

When we went to production to deploy on our side, we did it ourselves, with Denodo's help, because it was included in our license.

Yes, we saw a return on investment.

Depending on the size of the client you want to work with, it can be prohibitively expensive at times.

I am not sure how much it costs right now, but we did the PoC to justify purchasing the solution. It was approximately 1 million reais.

I would say that it is critical that you have some business model built, because it will guide you on how to implement the data sets in Denodo because you need to consume several data sources, but you must put them in some way that has some meaning to the business, you must migrate from physical modeling to logical modeling and business modeling. 

I would say you should incorporate these three layers into Denodo. To take advantage of Denodo, you must consider these three layers. Otherwise, you will just put some data there and no one will find it.

I would rate Denodo 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.

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 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.

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.

We use this solution as an access layer and virtualization layer. We connect to a number of sources and then use Denodo as the main access layer for consumers or for reporting. I have also personally used it for integrating sources for some of our critical reports which was a use case outside the regular virtualization capability. We calculated some of the key metrics for our critical components. I'm a data solutions architect and we are partners with Denodo. 

The strength of Denodo is that we can connect to a lot of different sources; it easily integrates and directly connects. It's great that it can flatten a JSON file and present connectors with a view format for downstream consumers. I would say reading or connecting to various sources and presenting a tabular view is an awesome capability. It can also be done with PDFs. The product has a good technical data catalog. 

I think Denodo needs a bit of work with performance management. When data sets are huge and a heavy query has been pushed out to the database, it can take quite some time to get what you need without clear optimization techniques. It requires clearer instructions. Some features should be added on the performance management and optimization side of things. I'd like to see them provide more on data governance. In addition, it would be good to have some support for analytical queries in SQL as that can be a challenge at times. There is currently no advanced analytic support for the SQLs.

I've been using this solution for two years. 

Denodo as a platform is stable overall. It can be a challenge if there are hundreds of users running a lot of queries, and then one of the queries suddenly sucks up the resources. When that happens, the system fails and there can be a risk to the source. 

If you have the product on the cloud, it's easily scalable. The risk is that because Denodo connects itself to some source databases, if there are multiple users,  then fired queries are delegated to the source which is a risk to the source. Denodo itself can scale up or down if it's on the cloud. We have close to 100 users on a daily basis. 

We have a separate operations team but I have connected with Denodo support and they were helpful. They were knowledgeable about the product. We were able to directly interact with their technical teams. So anytime we raised a ticket, we got a fairly quick reply and they were able to resolve the issue promptly. In the early days, our operations team connected with the Denodo technical team once a week to run over any issues. They were quite helpful with that.

We also use DBT, which is a data build tool with a similar function in terms of creating views on SQLs and then deploying on Snowflake. Both DBT and Denodo are popular because both of them are heavily SQL-based. If you only use Snowflake, DBT is preferable to Denodo. But if you're integrating data from different sources, Denodo is likely preferable.

I wasn't involved with the company's implementation. Deployment was pretty straightforward when I implemented it on my laptop. There wasn't much to it; you install it, and it starts working.

This is an expensive solution although I'm unsure exactly what our licensing costs are. Denodo is set up in nodes and each node is extremely costly. 

We're still trying to find a place for Denodo within the organization's architecture. If you have a very clear use case, it's a good product. In terms of data virtualization, I think it's very well-rounded.

I rate this solution seven out of 10.