Denodo Reviews

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 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. 

I am using Denodo as a data integration and management tool. The concept behind Denodo is data virtualization, which makes the retrieval of data available faster. The availability of data in real-time is much faster as compared to directly accessing the data from the web.

The virtual layer or Symantec part of it are most valuable. Where all the data sources, which we integrate together, are available on a virtual layer and that makes it faster.

I would like to see a connectivity option with third-party apps, for example, JDBC, and ODBC drivers. Currently, we need to install it separately from the Denodo side and then connect it. If they provided an option directly in Denodo to connect to these Power BI, and Tableau, Denodo would be even stronger. Microsoft provides SharePoint, and they have this option where you can directly connect to Power BI, and you can directly connect to the visualization tools. If Denodo can do this, then it would be great.

I have been working with Denodo for over one year.

Denodo is very stable. I started working with Denodo a year ago, and I have not come across any issues.

The technical team of Denodo is really good. They are very helpful. I had some issues because I was doing my first project, but the Denodo team is cooperative and supportive. They immediately helped me with whatever issue I was facing. I just had to email them, and they responded immediately.

Positive

It is very straightforward and easy. They provide hands-on training and proper documentation. Their knowledge base is detailed and easy to understand and learn.

Both options are available. The Denodo team can directly do it for you, or you can do it from a third party who is experienced in it. It takes one day, less than one day. You just need to know the right requirements from the customer for whom you want to deploy the Denodo platform, how many servers they want, and what type of installation they want. It depends on the customer, but the deployment is easy.

There is an express edition and an enterprise edition. For customers, obviously, we provide them with the enterprise edition. Students can use the express edition and it is free to download.

I would suggest having basic knowledge about data. For example, what are the different types of data sources? And what is a data warehouse? The fundamentals of data science. The basic knowledge as well as having an understanding of Structured Query Language, because Denodo uses a query language that is called Virtual Query Language, and it is similar to that SQL. I would rate Denodo a nine out of ten.

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.

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 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.

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.

Currently, we're working for one of our industrial resource clients. It is a hospital-based company that does resources and mining worldwide. So we use Denodo to create views for multiple courses so that clients can review them within two seconds.

We use Denodo to build our views. Before our views relating to GBT ODBC, we sometimes used mosquito bites and XML or flat files.

The ability to transfer data is very valuable. It is one of the best when considering other ETL tools and is easy to maintain. Compared to Informatica and Oracle Data Integrator, Denovo is the most convenient.

We can't scale it to meet digital requirements.

We have been using this solution for one year.

It is a stable solution.

It is a scalable solution.

It has a very straightforward setup. However, in some cases, it may take some time, depending on the database and variety of data.

I rate this solution an eight out of ten.

I mainly use Denodo for data modification.

Denodo's best features are its performance, easy data transformation, and the job scheduler. 

Denodo has some difficulty supporting large numbers of records. Its error reporting is also unreliable and doesn't give clear information on the problem. We've also recently had an issue with roles getting deleted.

I've been using Denodo for almost fifteen months.

We've recently had some problems with slowness and instability. 

Denodo is scalable.

The initial setup was easy and took about an hour.

I would rate Denodo seven out of ten.