Denodo Reviews

The idea behind data virtualization is to create an abstract layer for easy consumption by BI tools such as MicroStrategy, Tableau, Power BI, and others. This abstraction layer aims to avoid the complexity of directly accessing data sources, thus simplifying data integration. Denodo facilitates this by mediating between different data platforms like Teradata, cloud data warehouses, Oracle databases, and others, unifying them under a common virtual layer. This enables seamless access to unified data across diverse platforms and technologies.

Furthermore, Denodo includes an optimization engine that enhances performance through techniques such as static and dynamic optimization, cost-based optimization, and caching mechanisms. These optimizations help improve query performance, reduce memory usage, and enhance overall system efficiency. This optimization capability is a key feature of Denodo and other data virtualization tools, enabling efficient data access and integration across heterogeneous environments.

Denodo provides several server connectivity options with other tools such as ODPC and UDPC. It supports API integrations, allowing integration with a wide range of databases using different technologies, including NoSQL and relational databases. For databases that do not have a universal connector, Denodo allows users to create custom JDBC connectors. Additionally, it supports integration with websites using KPI connectors on-premises, offering a variety of connector options.

They need to invest more in the optimization engine. It will be a fantastic tool for them to enhance automation and improve the GUI interface, especially for Integration, as some tools are still not fully integrated, such as Iceberg. Batch processing is very good but not yet fully integrated. Therefore, they should focus on improving the GUI interface, enhancing cloud capabilities, and integrating modern technologies like Iceberg. Additionally, they should continue refining the optimization engine itself.

I have been using Denodo for three years.

It's a very stable tool. We faced problems related to vulnerability checks from the operating system itself, which were quickly resolved. It's robust and stable; we haven't encountered any major issues with it. We did need to allocate additional memory to handle our data volume.

I rate the solution’s stability a nine out of ten.

Denodo is scalable and supports load balancers for achieving scalability through multiple load balancing techniques. In our production environment, we have thirty-two cores distributed across four machines, each with eight cores. These machines are managed using a load balancer tool to ensure scalability and efficient resource allocation.

I rate the solution’s scalability an eight out of ten.

They provide extensive documentation which covers administration, development, and support comprehensively, providing detailed explanations for every step. In contrast, other data virtualization solutions like Data Virtualization and IBM Data Virtualization often lack such detailed documentation, which is crucial for implementing solutions to various problems. Additionally, Denodo provides excellent support. They have a dedicated and knowledgeable staff who are readily available when needed.

Positive

I have experience working with telco data visualization and analytics. I've utilized Denodo for data integration and analytics in telecommunications. Additionally, I've worked with mobility and IoT technologies for revenue assurance and management. I have proficiency in the Microsoft Stack, including SSIS, as well as experience with AWS Cloud services.

The installation is not extensive. It takes about one week. The entire project deployment, including development, usually spans around six months. For instance, development itself might take approximately three to four months, with the remaining time allocated to post-production tests, use case implementations, and other activities.

They have achieved significant improvements in KPIs, such as customer churn, reducing it by approximately eight to twelve percent. This is an actual figure. They have also increased customer loyalty by the same margin.

Denodo is expensive.

I rate the product’s pricing a six out of ten, where one is cheap and ten is expensive.

The main motivation was their use of multiple technologies such as SQL servers and Oracle, spanning nearly twenty-five different databases. This multitude of data sources and information spread across various databases necessitated robust data integration and visualization capabilities. Denodo played a crucial role in enabling the bank to unify and visualize information from these disparate schemas and technologies. This achievement significantly enhanced their ability to derive comprehensive insights from the diverse datasets. Numerous insights and use cases have already been successfully implemented across various departments within the bank. These initiatives have encompassed areas like predictive analytics, customer behavior analysis, and the development of machine learning models for HR and revenue forecasting.

Denodo's products help reduce time to market for new products and promotions, ensuring they reach customers promptly. This prevents revenue loss, especially at the customer and complaint levels, among other benefits.

Denodo has three layers of security. It is integrated with Active Directory for authentication. It supports single sign-on within the organization, particularly in the banking sector, where it is a leader. This integration allows for auditing and monitoring of all staff members. This forms the first layer of security. The second layer involves fine-grained access control over specific tables, views, and even columns. Denodo provides specific controls to determine who can access which tables and columns at a granular level. The third layer consists of generic governance rules governing user groups such as development, operations, and administration teams. For instance, developers may have read-write access, administrators have full administrative privileges, and operations staff have predefined access rights. These rules govern the authorization and authentication processes within Denodo.

Denodo is not an expert in AI nor does it propose AI-specific use cases. However, its abstraction layer can inspire ideas related to AI, such as predictive analytics for customer behavior, complaints analysis, churn prediction, forecasting future revenue trends, and identifying new customer benefits for a bank's portfolio, for example.

It provide a six-month warranty post-production, followed by five years of product support. This includes updates, new batches, upgrades, and more. One admin and two development team are required for maintainance.

Overall, I rate the solution a nine out of ten.

We use Denodo in our organization whenever a web service is needed quickly, or where using another technology (such as Java) would take too much time. From our standpoint, Denodo is used in such a way that any consumer can build their own web service based on their data points. There's no need to ask the provider, "I need a web service for X, Y, or Z". Instead, you simply ask, "Hey, I just need the data points". For example, for a table, all you need is to ask the consumer to provide the table name and for whatever service you need, you can build your own web service on top of it.

It takes minimal effort to accomplish this with Denodo and it's an extremely quick process, especially when compared to doing the same thing with Java or any of the other technologies we are using. In fact, you can build a web service with Denodo within 10 minutes. Our web services can also be consumed via different methods where there are multiple possible levels of responses, and each web service can be duplicated to provide for each different level of response. So within 10 minutes, you can build a web service with different variations out-of-the-box. 

If you wanted to incorporate just one method in Java or AWS, it would take at least a day to deploy and have it set up to provide responses. But our experience with Denodo is that it only takes a few clicks and it will instantly deploy the web service, and then you are free to use that resource. 

As for our environment, there are two editions that we have the option of using. One being the cloud-based version, and the other is a client version which we can download onto our system. Most of our organization is using the cloud-based version, as all the patches are pushed directly to the cloud. Overall, we have about 100+ company members using Denodo, most of whom are product developers.

We have web services created for each of our applications, and ordinarily the creation of these web services would be dependent on the provider. We would previously ask our providers, "We need web service X, Y, or Z, and we need it by this deadline. Can you produce it by that deadline?" But now, the person who needs the web service can simply build their own based on the data points they are looking for. This kind of mindset is the main reason why we chose Denodo.

The best thing about Denodo is that creating and deploying a web service can be done in about 10 minutes, compared to a whole day when it comes to other solutions (such as when deploying with Java and AWS).

It's also really easy to do so in general, because no longer do you need to request the specifics of how the web service is to be created, but instead all you need to do is provide the data points needed and you will have access to a web service that is ready to serve you responses.

Not only that, but you will also be able to duplicate the newly-created web service to be used in different ways with various methods. And all this takes only a few clicks on a single platform, as long you know the data points that you need.

There are a couple of areas that can be improved in Denodo. From a stability point of view, sometimes we see issues in the data management functionality. This only happens now and then, however, and usually takes place when we add in our own customization.

There are also certain limitations on customizing Denodo, in general. It would be better if Denodo provided more mechanisms for users to develop custom products where they could easily build in their own logic with automated means. In the case of complex customization, we will usually use Spring Boot instead of Denodo, especially when we have tons of data in production and we need to segregate it based on certain logic. Otherwise, when it's a matter of minimal data points that are required, we will simply build it as a web service instead of writing the same logic in Spring Boot.

A feature that we have wanted since we started with Denodo is to have a fallback option. After we migrated all our web services to Denodo, it would have been nice to have a ad-hoc fallback option where if we ever do want to use something else, that option is available. For example, something where we have those built-in read-only views which we can reuse and, without too much time or fuss, build a web service on top of that by simply plugging in views, details, or any other part of the Denodo platform architecture.

I have been using Denodo for one year now.

At certain times we have seen some stability issues with the data management within Denodo. It's not all the time, of course, but only sometimes.

When it comes to more complex scenarios, we will typically use Spring Boot instead of Denodo to accomplish our needs. Usually, this happens when we have tons of data in production and we need to segregate it based on some logic.

With regard to scalability, we have different scaling strategies for two of our main products that we're working on. There isn't much difference in data points between these two products, but when it comes to the refreshing of the data, one of the products is refreshed on a minute-to-minute (or second-to-second) basis. With this product, the scalability of Denodo isn't fully up to the mark.

However, on the other product, we have no challenges whatsoever in terms of scalability, especially in terms of response times and accuracy. We have built a lot of web services on top of it with Denodo. 

When we purchased Denodo, our architects had a discussion with their support team based around what would be needed to improve things, such as scaling up at a later stage, and they were happy to help us out. We also occasionally write them emails whenever we encounter a challenge such as a code glitch, but otherwise there is no further direct interaction with them for the most part.

Denodo is one of the only products we have come across where the consumer can build in a web service without being dependent on the product team or anyone else. If you know the table name, or the data points needed, you can directly go ahead and import the schema and build your web service. Crucially, you don't have to wait for someone else to come and help you build the web service, which ultimately reduces the dependencies between our different teams.

This is, in fact, a main focus point we have come across in our work. In terms of data points, we will typically see 100+ data teams working with independent databases with no platform to connect them all. With Denodo, we can connect hundreds of databases with the data point connection, and it's all drag-and-drop to connect tables from whatever database we need. Then we just export the web service on top of it.

You can contrast this process with Spring Boot where you would instead need to go to a specific team and get access from them first. They would then have to take the name of the table and report it elsewhere in another format.

Of course, we also prefer Denodo for the simple reason that it is cross-platform across the different platforms we typically work with, which have extremely specific conditions when it comes to handling data.

The setup includes what is essentially a kind of software installation. If you go for the cloud-based tool, it's not much of an installation at that, because you just plug in your databases and you're ready to start working with it.

It's very easy and very fast. Basically, you are just plugging in the databases and setting the location of the cloud-based URL which will be shared by your team.

Denodo provides a lightweight 30-day free trial, but when we do courses on top of it, it costs $150 for each person. Even if you're not purchasing the product, I believe there is some kind of reward they will give you in the initial stage.

I, personally, am doing a couple of courses with them and each course costs a different amount depending on the level of the course, such as beginner, medium, or senior. The initial course level costs $150 and the mid-level course goes to $200, and I have seen a couple of courses at $350 as well. These costs are incurred as you enroll in a single course, which lapses after six months.

To people thinking about using Denodo, I would say that you should be clear about whether it fits the level of your architecture in terms of scalability. In cases where you have a low-level architecture, you shouldn't expect to get more results out of it simply by using Denodo.

Essentially, when you're building a product, your environment should be appropriately scaled to fit that product, and Denodo is built for the enterprise level, not for small-scale inter-system users. For example, in our organization, we use Denodo for its web services functionality, but when it comes to similar products in the realm of event streaming, for example, we will instead use other tools such as Apache Kafka, as appropriate.

I would rate Denodo a six out of ten.

I use the tool to integrate and standardize data. It converts all kinds of data. It can convert non-relational data to relational data. It can create a standardized way to consume data.

The API generator helps generate APIs. The integration with Presto and other MPPs is valuable. It also provides integrations with Lucene and Elasticsearch. The tool has zero data replication. We can consume data fast. The product democratizes data. People talk about data democratization. Providing access to data is one thing, but the solution gives data in a format that people can consume.

Data transformation must be improved. Denodo is not the best tool for data transformation.

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

The product is pretty stable. I rate the stability a nine out of ten.

The product is highly scalable. I rate the scalability a ten out of ten.

The technical support is very good. I rate the support an eight and a half out of ten.

Positive

The setup is simple and straightforward. The deployment takes about two months. We required two data architects to deploy the product. The vendor maintains the solution. The tool can be deployed on-premise, in the cloud, or in multi-cloud environments.

By using more data in decision-making, our strategy became more accurate. Eventually, we can replace a lot of processes and a lot of systems that we have.

Starburst and Tray.io are too technical. Denodo is very user-friendly. Denodo is a technological tool for non-technical people. It is very easy to use. Denodo is way more mature than Starburst and Tray.io.

We connect all the data sources with Denodo, and Denodo connects with the metadata. We do not move the data. We embrace the fact that data now resides in distributed data sources. Through the metadata, we create a catalog. The catalog pretty much centralizes all our data management. Through the catalog, all the information is standardized.

We can visualize the information, manipulate the data, and integrate the catalog with data-consuming systems like Power BI, Tableau, and Apache. We do not centralize data. People think we need to get all the data outside the sources and put it in a repository to manage data properly. It is not necessary. We can integrate and create the catalog without replicating or moving any data. We can integrate with all the data-consuming systems we have and create a logical data layer.

Overall, I rate the solution 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.

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. 

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. 

I work with business views for different areas.

Denodo is a good tool for data virtualization and cataloging. Its catalog is useful for data governance and helps document information for databases and fields. 

Denodo is also effective for developing solutions quickly, facilitating user reports, and offering good data governance. It provides useful APIs and integrates with other systems.

The cache configuration is more complicated.

I have used the solution for two years.

Denodo has good support with the vendors and it is timely. They have a good methodology for learning how to use the tool, and the documentation is very thorough.

Positive

It is easy to set up.

Overall, I would rate Denodo a nine 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.