Talend Open Studio Reviews

The data quality features are quite noteworthy. Data quality features are important.

There is a need for mastery in some areas.

Stability feels fine.

Customer service needs a better approach.

The initial setup was okay.

The implementation team used Studio.

The setup cost is expensive, so there are considerations.

I'd rate the solution eight out of ten.

I am using Talend Open Studio for ETL. I extra data from APIs and transform it for the data warehouse.

The most valuable feature of Talend Open Studio is the tMap component. There is a lot of functionality in one component.

The stability of the solution could improve when running jobs. There can be errors when running projects but in the end, it works well and the errors do not impact the result.

I have been using Talend Open Studio for approximately one month.

There are times in our usage when the solution crashes. When we are running jobs that are more than one or two it can crash or not work well.

I rate the stability of Talend Open Studio a five out of ten.

We have approximately eight people using this solution in my company.

The solution is scalable.

I have used Informatica before Talend Open Studio and when comparing the two, the interface is more intuitive in Talend Open Studio.

The setup of Talend Open Studio is simple. The process took approximately two hours and it was my first experience.

I rate the initial setup of Talend Open Studio a ten out of ten.

I implemented the solution.

I am using the open-source version and it is free.

The solution does not require any maintenance.

I recommend this solution to beginners. It is free and the interface is intuitive and has a lot of helpful components.

I rate Talend Open Studio an eight out of ten.

We are currently using the free version. We use the solution to extract loads from the source system into the entire house. We are also doing API and data integrations from TXT or XML files.

Though we are not currently using it for big data, there is a plan to extract data from MongoDB.

The API integration and big data approach are very good because of how you extract data from JSP files or big data web repositories like MongoDB. This is an excellent tool for big data and API integration.

Comparing Talend Open Studio with SSIS, Informatica, or Data Services, I think the overall workspace concept can be improved since these other solutions have workflows and data flows.

I have been using Talend Open Studio for the past three months.

The solution is stable enough. It's a mature tool. It is a bit complex in a few areas, such as when writing your ETL Jobs, because tLoop is slightly confusing.

I have used SSIS, SAP Data Services, and Informatica to a small extent in my previous companies. My current company uses Talend.

We currently use the free version, where we don't get the built-in scheduler. We had to deploy the job on the server as a file and, using the CRON jobs, schedule the batch or shell file. We can deploy the solution and the ETL jobs in ten or 15 minutes.

We are using the tool's free version because the enterprise version is a little expensive.

You would need three enterprise servers if you are going for a full-scale lifecycle, like development, quality, and production. That would be expensive because the servers have yearly costs.

We can only have one user in the free version. We are now wondering whether we should go for the enterprise version or switch to a different platform, like the HANA platform, HANA cloud, or Datasphere. Or another platform called Encarta. There are multiple technologies we are exploring.

It's a good tool overall, but that depends on whether you have the enterprise version. The free version is not for a team in which you have more than one member. In this case, you have to go for the enterprise version, which is a bit expensive.

Likewise, you do not get support with the free version, so you won't speak with tech support. There is, however, a community with a knowledge base in forums.

You also get the scheduler, the deployment, and everything with the enterprise version. You could deploy the solution on the server and then schedule the jobs. Likewise, you get logging and an audit trail of your jobs. Currently, we maintain these jobs manually.

They should make purchasing the servers for the enterprise version a one-time payment, where you buy the server, and that should be it. The yearly cost is what makes Talend not a great tool.

Talend is fine if you are only using it for the ETL tools. However, there are other options, such as SSIS, Informatica, and SAP Data Services, which are not promising for Talend Open Studio. Some things are easier with other tools. Talend is logical, but a few things are not very straightforward. If there is an option to choose from other ETL tools, I would rate Informatica number one, in second place, maybe SSIS, and then maybe Talend.

If Talend Open Studio is cheaper than other solutions, you can go for it.

By being able to cross-match records across multiple data sources and create a logical dataflow with options to place rejected records in a separate table, we are able to cleanse and create golden records in multiple categories. Rejected records, once identified, can be assessed for repair. This also means that we can identify how and where the rejected record occurred.

The Talend Studio connected to the Talend MDM (Master Data Management) is the most valuable feature. Talend Studio is used to create a job stream that connects to multiple data sources, matches, compares or creates a golden record for overall identification. It also has a good catalogue of objects that can be dragged and dropped for building models.

It needs better installation configuration for other databases. Although the installation allows you to select another database, this doesn't mean that all connection points in the application point to the database selected. You actually need to do a search through the entire install to locate the configuration settings and change them.

In version 6.2 we did encounter issues with the job servers and specifically with ESB. Version 6.3 is better but large jobs can cause the MDM server to fall over, requiring a reboot.

We've built in some self-healing scripts to detect a loss of connectivity and force a restart of the services.

Our Talend installation has been deployed onto Red Hat OpenStack, separating out MDM, TAC, DQ, and thee job servers. I made a point of determining data storage requirements for each server, and a memory ulimit setting to match the resource profile of the components. It was trial and error but it paid off by allowing the Talend system to process large jobs of 200-300 million records over a number of hours, rather than days.

Support tends to be good for the usual types of issues, but once a problem gets more complex and deeply into the nuts and bolts of the product, support struggles.

Initially we used Pentaho, however, it was determined that this was not as feature rich as Talend.

The initial setup out of the box is straightforward. However, it becomes more complex as you start to distribute the components and get forced down a path of connecting to one type of database for all the components. In my case, I had to deploy Talend using RedHat Ansible and use only a PostgreSQL database.

I needed to first install the software, search for all references to H2 or PostgreSQL, change the configuration files, and then do it all over again for the distributed installs; then translate this into Ansible scripts. So although it's not directly Talend that made this complex, the installation by Talend gives the option to install to PostgreSQL but doesn't use PostgreSQL for all database repositories.

Pricing and licensing are fairly straightforward. It is reasonably priced and managed. It's a good solution overall.

Pentaho, and prior to that SAS MDM which was similar but it was harder to create models. We also ran a PoC for IBM Infosphere MDM, but the cost was considered unacceptable.

Make sure you have someone with technical skills and patience to install in a distributed deployment. Learn the product well and build in your own log shipping with either Splunk or Elastic or Telegraf to ease your diagnostic pains.

I use the open-source version of this solution. It's data integration-related. Right now, I'm doing some legacy TL into a new enterprise data repository.

When the tool has an error, the error-handling is not that user-friendly. It might just be my inexperience with the tool, but I struggle a lot with finding my layers sometimes. I think my biggest problem with the tool is that the errors are very hard to debug.

Our special need is geospatial data, so that could be included as part of the tool and not only as an add-on. It's always hard to do add-ons and tools when it's a third party, and every time there's going to be an upgrade, you don't know if it will keep working. It would be great if they were included as part of the main tool, like FME. That would be my main concern about the Talend tool right now.

I have been using this solution for about a month. 

The solution is stable. 

The solution has add-ons that you can add. I'm dealing with geospatial data, and you have to have add-ons to do that, but I haven't gotten a chance to add them yet. The first add-on I tried didn't work, but I think it might just be outdated and not compatible with the version of the product that I have.

There are two of us using this solution, my colleague and myself, but in the next month or so we are going to get the Professional version in a private cloud environment. We're exploring the tool to decide if it's going to become our tool of choice for the data repository and data warehouse. Right now, we're working locally with the open-source version of it, but we're trying to decide if Talend is the right tool for us and in order to do that, we want to have the proper version of Talend in the proper environment and then do all the tests.

FME has been used for a long time at my company, strictly for managing geospatial data. Now, we're creating an enterprise repository, and we need to deal with the regular data plus the geospatial data together, so we're trying to find a tool that will be able to handle both of these types of data, and manage all of the enterprise requirements that we have. We have used solutions like FME, but I don't believe there was any other tool that was used on the scale that we're trying to use Talend now.

The initial setup was pretty straightforward. I didn't have many problems installing it. It seemed very straightforward to me. 

Deployment can take a few hours, depending on your environment, because it requires some things that you may need to install if you're missing them. I think it took me probably under an hour to do it.

I did the deployment myself on my local workstation. 

Right now, because we're using the open-source version, there's no cost. However, down the road when we use the Professional version, there will be costs. I don't know what the cost will be because I'm not involved in that, but I know that there is a license at that point.

I would rate this solution as a seven out of ten. 

We use the solution for integration, warehousing, and enterprise service costs.

The technical team uses media resources from Facebook and other social media platforms for ETL.

It is easy to use and covers most of the functions needed. We can use the code without any extra effort. The open source is very good. They have the same commercials with additional connectors. The graphical design environment is also very easy.

The solution needs more integrations.

I have been using Talend Open Studio for two or three years.

The product is very stable.

The solution’s scalability is good. We have five users and are building ETL integration and design to implement with another system. We have three licenses for developers.

We worked with the SSI, but it had very few primitive integrations and was hard to use. We switched to Talend because of the integration of two-way communication. You can add components for that warehouse for the quality. It is a complete platform for integration.

The initial setup is very efficient and takes about a half day to complete with configuration and needed components.

Talend gives you what you want without hiring new people and offers extra services. They train mid-senior developers to use it perfectly.

The product’s pricing is reasonable. It has an annual subscription.

I recommend the solution because it has a huge community in which to get support. We have additional connectors from the community and support.

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

We use it to construct a robust data warehouse. This involves seamlessly integrating data from diverse sources into our data warehouse. It plays a crucial role in ensuring data cleanliness and quality throughout the integration process. We also use it for effective fraud detection measures, further enhancing the reliability and security of our data warehouse.

The standout feature for me is the user-friendly nature of the components. They make the entire process exceptionally easy. Another aspect I appreciate is the scripting part, where Java code can be written. Many of the components I've utilized, especially those for data connections and recommendations to various sources, have proven highly beneficial. The capability to seamlessly integrate Python code within Talend Open Studio adds another layer of versatility.

When faced with a challenge, such as the necessity to link up with an unconventional data source like the legacy Cyprus Vision database that wasn't inherently supported by Talend, I had to resort to writing Python code to establish the connection. The administration console could potentially streamline payment management processes.

I have been working with it for ten years now.

The stability provided is excellent, we didn't have any issues with it.

It provides good scalability capabilities.

We used DataStage some time ago. More recently, I've also had experience with Microsoft Integration Services. Upon comparison, I found Microsoft Integration Services to be more user-friendly in comparison to DataStage.

The initial setup was straightforward.

We simply download the tool and place it into a designated folder. After setting up, we execute the tool and commence job development. Once the job development phase is complete, we build the jobs, generating a Java file that can be further exported to a job scheduler for seamless integration into our workflow.

The cost, particularly in Africa, is quite high.

Overall, I would rate it eight out of ten.

We primarily use the solution just to pull the data from the source to the landing zone. We are using the administrative console as well.

The profiling perspective needs improvement. Instead of using it in the studio, we are using a different tool which is also provided by Talend. It's redundant. They should remove that from studio to make it more lightweight or improve upon its interface.

The two things that Talend lacks is an MDM and the CDC. I know Talend has both of them, but both of them are not exactly usable in actual scenarios. I know that Talend has some integrations with other companies for MDM, but I'm not sure what they're doing for CDC. Maybe Talend can work something out regarding the CDC feature. I know the solution has its own CDC, but they're not focused on it as much as people would like them to be. I would like to know what their plans for it are or if they plan to partner with another organization to market it.

Currently, the solution is stable. However, three or four years back, it used to be a bit unstable. The software is quite stable as well.

The solution has quite a good range of scalability. The jobs are quite scalable since we have now integrated them with Docker so we can follow all the principles of microservices. 

We have a license for five users. We have someone focused on data quality. Someone else is looking into the solution as a tester, and testers are working on the stewardship tool to correct the data and verify it with the business. Then there are two free developers who are solely working on the Open Studio to turn out code. 

We do have plans to increase usage.

I don't have any complaints with technical support. They've been very responsive.

We previously used to use a wide variety of solutions, including Informatica.

The initial setup was quite straightforward. The deployment took between two and three days. 

We deployed it in our Unix boxes using a third-party tool called Jenkins.

The whole deployment model is automated and it happens every three weeks. There are just two people needed for maintenance.

We are the consultants. We handled the implementation ourselves for our clients.

There are costs above the standard licensing fee, for example, if you need storage space.

We evaluated other options, such as Azure Data Factory.

We are using the AWS public cloud deployment model.

I would recommend the product. As long as you follow the best practices you will get what you want out of it.

I would rate the solution eight out of ten.