Talend Data Fabric Reviews

We are involved with multiple vendors, including Talend, Alteryx, and Informatica in the data management and governance space. In the classification and governance area, we use BigID, Spirion, and several other products as well.

Regarding Talend Data Fabric, the ease of use and the customization options that are available are particularly valuable. There are a lot of built-in components and features that we can modify in any way we want to transform the data and make it analytics ready.

Talend Data Catalog is another product that, when combined with Talend Data Fabric, can be used for the data governance piece. The stewardship, ownership, and curation happen mainly from the Data Catalog side. Within Talend Data Fabric, the role-based access control is used for user segregations such as security infrastructure-related or integration-related activities. It bifurcates the roles and responsibilities. From the data standpoint, the RBAC functions with the help of Data Catalog.

One thing I found missing was integrations with SAP systems. We have extensively implemented one complex SAP project with Talend Data Fabric. At the same time, there were some complexities there, and certain optimizations were requested. Support is something that drives me crazy these days. Since Talend was acquired by Qlik and Informatica by Salesforce, both the support teams have taken a back seat.

I have used this solution for over thirteen plus years.

I will put it this way: the support I get from the pre-sales team of Talend is prompt. Whenever I reach out, they will respond. However, the actual support team who resolves the tickets takes some time. Initially, the support was very good, and I would have rated it nine out of ten at that time. Currently, I would rate the support in the range of five or six.

The deployment or implementation part majorly depends on the project complexity and the client data that we have to handle. Based on that, it will vary. There are some projects where we have wrapped up in three months, but there are some projects that we have wrapped up in one and a half years. It obviously depends on the client requirements and what kind of data we are dealing with.

Compared to other solutions, the Talend pricing model is changing from user-based to capacity-based. User-based licensing cost was much less compared to Informatica. The capacity-based pricing will be in similar lines, I think, close to Informatica.

Initially, we were majorly using on-premise solutions and then we have moved into cloud deployments. It depends on the client and their requirement, whether they would want to go ahead with an on-premise only solution or cloud.

Deployment for us is simple. We have done major deployments of Talend Data Fabric in this region.

Regarding real-time capabilities, we have not done many projects in that area. We did a few with Kafka or Spark streaming in the initial days, a few years back. However, after that, I have not personally much used the real-time capabilities of Talend Data Fabric.

There are certain components which help us to get the data quality checks done, and we extensively use those. Overall, I would rate Talend Data Fabric nine out of ten. I was able to accomplish a lot of my complex things using Talend Data Fabric, so it is always a go-to product for me. I would give this review an overall rating of nine out of ten.

I am currently phasing out of Talend Data Fabric, as the client where I have worked for many years migrated out of Talend this year into a different tool. I have helped the team to migrate out of Talend, but it had been working on Talend Data Fabric since approximately ten years ago. My use case is now diminishing because we are phasing out and it is being decommissioned at the client where I work.

I am switching from Talend Data Fabric to something else. Since Talend Data Fabric went integrated into the Click package, the licensing became too expensive for the client to afford, and they decided to move out of the technology based on those pricing elements.

The client is migrating from Talend Data Fabric to several solutions. The client has too many sectors, and some parts moved to Informatica while others moved to DBT. I have been more in contact with DBT, but it is not the same thing because it is not only DBT; you need to enclose AWS Glue as well for the ingestion phases, and DBT only plays the transformation role.

From my experience around Business Intelligence for data and analytics for around twenty-something years, I can say that what I appreciate about Talend Data Fabric is that we can connect sources to everything and be able to customize everything. The freedom I have as a developer is what pleases me most regarding Talend Data Fabric, as I always find a way to customize a component to meet my needs. The downside, however, is indeed the pricing, which has been the biggest challenge; since it went to Click, there is no longer a free license version such as Talend Open Studio, so either you pay or you do not have anything.

Regarding the downsides of Talend Data Fabric, I think they can improve overall pricing. It is a challenging question to answer because, while I see advantages, the disadvantages revolve mostly around pricing and the fact that it operates on top of Java, which means I need to have my own server to execute processes. The management of memory is also not easy to monitor, and developers need better tools to tune memory and understand what they need to do.

I have been using the product for approximately ten years.

Talend Data Fabric has been quite stable for us, with all our services and servers restarted every week, so there were no noticeable lags or crashes.

Scalability with Talend Data Fabric is limited because scalability depends heavily on memory usage. If my project consumes a significant amount of RAM, scaling up is not straightforward as it requires changing the code. This makes it a challenging task to manage scalability effectively.

In the past, I contacted the technical support of Talend Data Fabric, primarily through a dedicated team within the client that handled vendor relations. Most of the issues were reported by that specialized team to the vendor, allowing me to focus on my work without directly reaching out to support myself.

Positive

I am switching from Talend Data Fabric to something else.

The initial deployment of Talend Data Fabric was somewhat difficult when I set up version 6.1.1 since there was not much knowledge and the team required help from Talend Data Fabric's professional services to guide us through best practices. The challenge was setting up a new tool while lacking knowledge and guides to help us independently implement the tool in an enterprise project. We faced approximately four or five version migrations, where each new release required us to go through our code, which is painful for projects with more than three hundred jobs to manage, compile, and publish.

The biggest difference between Talend Data Fabric and my current alternative is the licensing model. For instance, I previously required a developer license for each developer, but now, I pay by project regardless of the number of developers. This facilitates scalability without having a large budget impact, which is important for big clients.

At the moment of phasing out Talend Data Fabric, maintenance from my end is not applicable. A new user would need to monitor the drivers associated with the tools being used closely. For example, if connected to a frequently updated database, failing to update the driver could lead to issues down the line. Therefore, it is crucial to plan a roadmap to keep drivers and connection strings up to date.

Everything I mentioned applies to the current version of Talend Data Fabric right now. The technology is different because it is more on top of the cloud version, where I do not control the migration process; it migrates by itself, and I must deal with the consequences. While the tool is always up to date, I need to know the best practices to avoid breaking my code with every new version.

I previously had a partnership with Qlik while working with Talend Data Fabric, using Qlik Sense for many years. However, that partnership is not active at the moment, as we are phasing out from those tools.

I would rate this product a seven out of ten.

The main use cases for Talend Data Fabric include setting up a data lake to enable the data platform.

Everything in Talend Data Fabric is GUI-based, making it very user-friendly and easy to learn quickly. Talend Studio is extensively used, and the admin console allows me to handle everything, including setting up tasks and scheduling orchestration. These are crucial parts of the product.

Data governance is still not mature. There is not much documentation available for it, and the maturity of the product does not meet my expectations. Master Data Management has been decommissioned, leaving gaps in the governance area.

I have been using Talend Data Fabric as an ETL tool since 2013, and I have a lot of experience with Talend Data Fabric.

When certain tasks are scheduled, they may go into a sleep state, requiring manual monitoring and rerunning. This is a concern, but otherwise, I don't see other challenges.

Horizontal and vertical scaling are possible, so scalability is not a challenge.

The support is not very good. The team is not well-trained, and resolving a ticket can require several discussions. They often ask for information repeatedly and are reluctant to join calls.

Negative

One person is sufficient for the setup.

There is definitely an ROI, and it is more than thirty percent.

The solution is a bit expensive but not as much as Qlik Replicate.

I would rate Talend Data Fabric eight out of ten. I am just a user of the product and do not have any partnership with Talend. There are multiple tools available for data governance, and improvements in this area could be beneficial.

Talend Data Fabric is more than just a typical integration tool; it's a comprehensive suite of tools that includes Talend Data Integration.

It supports API integrations, transferring data through APIs instead of traditional database methods. For big data, Talend can act as an orchestrator, spinning up clusters like Spark or Databricks to process large datasets.

Talend Data Fabric is ideal for organizations that avoid dealing with multiple vendors and tools. It enables users to handle all aspects of a data management project—from extraction and loading to governance and quality. With Talend, users can manage their entire data journey and complete their data management projects without needing to rely on additional vendors.

Talend can be used for multi-cloud purposes, allowing users to orchestrate data across various cloud platforms without purchasing AWS Glue, Azure Data Factory, or similar cloud-specific tools. With Talend, users can seamlessly manage data processes across multiple cloud environments and still maintain the option to use Talend on-premise, avoiding the need to invest in additional tools for on-premise operations. 

Talend's architecture is complex to configure, especially due to the various components involved. It requires a more intricate setup.

With Talend, multiple servers and components need to be properly synchronized and configured to work together effectively. This process demands a higher level of skill and experience to ensure that all system parts are correctly aligned and functioning as intended.

I have been using Talend Data Fabric for less than a year.

It is stable. I have not come across any major concerns about if it's glitchy.

It is easy to scale.

Support is good.

Positive

Informatica is a well-established product known for its stability. Hardware and configuration can affect its performance, and it's not a lightweight tool that will fail quickly.

When purchasing Informatica, you have options based on your needs. A simple data ingestion or integration license is relatively affordable, but the full Data Fabric suite is expensive.

The Data Fabric suite includes integration, data quality, API management, big data processing, and real-time capabilities. For those who don't need the entire suite, purchasing individual components, such as data integration or data quality, it is a more cost-effective option. These individual licenses are generally less expensive than the complete Data Fabric suite, offering a more flexible and budget-friendly choice than Informatica's flagship.

Deployment of Talend Data Fabric typically requires about one week of effort. After the sale, the process involves a post-sale offering where the previous company would handle the installation on the customer’s premises. This installation process generally takes around ten days to complete, given the complexity of the architecture. The setup involves various interconnected components, which can make the process more intricate.

With Talend Data Fabric, you can spin up a Spark cluster and utilize structured streaming to process data in real time as it arrives. This capability allows you to test and analyze data on the fly. Additionally, suppose you're working with APIs in real-time. In that case, Talend Data Fabric can reprocess data by connecting to APIs, making it a powerful tool for handling streaming data and API-driven processes.

One guy is enough for the maintenance. 

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

Data & ESB integration solution for a ecommerce company

ESB has been the distinguishing feature. We have implemented near to real time interfaces

The Talend data integration has been one of the most valuable features.

Compared to Microsoft SSIS which is a drag and drop solution, the finishing touches are not as refined in Talend. The way you search for pallets in Talend could be improved.   

We have used this solution for two years. 

This is a stable solution. We are currently using version 7.3.1, but preferred the version before. The problem that we currently have is that Talend are releasing patches for Talend Studio every quarter. Our technical team has to be on top of these patches and constantly ensure everything is updated.

This is a scalable solution. 

Talend support is good. We have an account manager who has been very responsive. Everything is driven by an SLA, so it all depends on the type of subscription that the company has taken. 

Positive

The initial setup is straightforward. 

There are multiple subscriptions available with Talend, each with its own scope. Subscriptions depend on the number of users you have and how many remote engines you want to install.

I would recommend Talend as an integration solution. Talend has very good support for big data. I would say Talend is just behind Informatica and Gartners Leadership Quadrant.

I would rate this solution an eight out of ten. 

This program is deployed in our organization on-premise and in the cloud and we use it for data integration and data quality purposes. We also use it to provide Business Intelligence analytics.

What I find most valuable about this solution, is the 900 connectors. Because it allows me to integrate any tool and any cloud system I need to integrate and they have a connector out of the box.

I would like to see better integration with other tools because every tool waiting for approval in terms of leveraging machine learning takes a long time.

I have been using Talend Data Fabric for around five years now.

We've had no issues with the stability so far.

The scalability is very good because you can scale on multiple servers without having to pay extra licensing fees.

We've used the technical support team a few times and they were very helpful. So I'm really satisfied with the solution's customer service.

I've used a few other solutions in the past, but I switched to Talend Data Fabric due to its flexibility in the development and manageability of not only developing workflows but also deploying, monitoring and managing them.

If you choose to start small, the integration is really straightforward. The initial deployment took us around two months. We did everything ourselves and without the help of an integrator. 

On a scale from one to 10, I rate this program a nine, because there is always room for improvement. Additional features that I would like to see included in the next release of Talend Data Fabric is having more machine learning capabilities inside the product.

We are using the on-premises version.

It is a smart tool for us to design data pipelines. It lets us populate our three data lake instances. We like this solution for its connection capabilities since it is very important to be able to use many different types of software. We tested a lot of SAP sources successfully, including cloud sources with SAP. It is also very easy to anonymize data with TIBCO, as well as populating HDFS files, packet files, and raw files. It is very easy to do that with Talend Data Fabric.

Deployment can be difficult, but I didn't test the latest version yet. With Talend products, every release brings a lot of new features and functionalities. This is never a small adaptation because the tool is maturing, but we need to test the latest version and to check its deployment capabilities.

It is our objective to promote all of the data pipelines. We have a design in production and this is our last concern regarding tool adoption.

This is close to being solved. It's just a matter of time. We have no technical issues. We have good support from the vendor.

Now maybe it would be good to work towards being able to use edge and to be able to deploy the pipeline designed on any platform, on-premises or in the cloud. I think this is their vision also. Adoption of the hybrid cloud is the direction we are going in. Creating a hybrid between the on-premises path and the cloud path so each was able to design something without taking accounts of the target would be amazing.

It is definitively a stable solution.

It is scalable because Talend Data Fabric is a code generator. This is not an engine as an Informatica Power Center is. This means that when you generate code, and you operate the code the caliber of the code is different.

This is a developer tool, so we usually have eight concurrent users.

To be frank, at the beginning, it was very, very difficult. Now, I think that Talend understands what our challenges are now we have a high level of support both in France and the Netherlands. I work for two airlines: Air France and KLM.

This is at the level of our expectations. That was not the case one year ago. Now the level of support provided by Talend is at the right level.

It is very easy to set up the product, it's not complex at all. But for the designer tool that we have on a laptop, the main issue is the java version. You have to have the right java version on the laptop.

The platform took a couple of weeks. When a developer wants to have the tool available on his laptop, this is automatic deployment time. We are able to deploy automatically. The tool is very easy. My job is not to develop it. I am an enterprise architect but I test and evaluate once every two months, just to understand how each tool works. When I have free time, which is unusual, I try to play with the tool that we have. For me, Talend Data Fabric is very easy to use. You don't need to have a lot of knowledge to use the tool.

The most difficult task is to get the credentials to connect the software. That is more of an organizational issue than a technical issue, though.

We selected Talend Data Fabric two or three years ago because this is the tool that has the most capabilities to work with all the Adobe modules.

We selected Talend because the objective was to populate the data lake and this is the tool that has the most capabilities to populate files and repositories of the Adobe platform. This was the driver when we selected Talend.

We needed a smart supporter because this is the first type for the users. The first time the user plays with the tool is always the most difficult period. We have a couple of experts to help with that. It is very, very important to have technical experts on the sources. If you want to connect an ACP source, for example, whatever the flavor, if you don't have your team or you don't ask the SAP expert, you will fail. This is very easy for a SAP expert, because the Talend documentation is very smart. You fill in talend.com and everything is well explained. If, however, you are not able to translate the recommendations in the figures of the source, it is very, very difficult. This is a one lesson that we learned. You need to have a experts, but it is not a full time job. When you want to connect to SAP source, you ask a SAP guy, he works a couple of days and the job is done. You definitively need experts for retrieving data, though.

I would rate this as eight of ten. It doesn't get rated a ten, because this is not a perfect tool. Each release brings new features and I think the tool is still maturing, but definitely in the right direction.

We use the product for extracting and uploading data into the database.

The product has valuable features for data connection, business queries, and schema management. It helps us create and load pipelines for certain data into the databases.

We encounter issues getting email notifications. They should provide enough information about the configuration process for email components.

We have been using Talend Data Fabric for two to three months.

The product is very stable. We haven’t encountered any issues while handling large-sized data. I rate the stability a ten out of ten.

I rate the product’s scalability a nine and a half out of ten. Currently, only one data engineer is using it in our organization. We plan to add more users in the future.

The initial setup is very easy.

I evaluated Oracle before. Later, we decided to go for Talend Data Fabric as it is an open-source and user-friendly product with high scalability. It has efficient support and integration services.

It is a good tool compared to other vendors. I recommend it to others and rate it a nine out of ten.