Talend Open Studio Reviews

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.

I primarily use the solution for integration. I consolidate data from several different databases and spreadsheets and merge systems into Amazon Redshift.

The solution has a good balance between automated items and the ability for a developer to integrate and extend what he needs. Other competing tools do not offer the same grade of flexibility when you need to go beyond what is provided by the tool. Talend, on the other hand, allows you to expand very easily.

We have a good integration with Artifactory and a good integration with GitHub. 

I don't see the need for anything. At the moment, Talend is a good complete product while at the same time not being overwhelming.

What I really don't like is the TAC, which is the Talent Administration Console. It's currently slow, old technology. It's obsolete and ugly to use. The studio is great, whereas TAC is on the other side of the spectrum. Actually, in AWS, in many cases, we are ditching the TAC and we are using Amazon-provided services, like Lambda functions, to code the Talend files produced by Talend Studio.

The server-side should be completely revamped.

I've been dealing with the solution for more than three years.

There are two pairs of version keys that parallelize, which is not available in the free version. However, when you can parallelize your jobs you can achieve a good degree of scalability. This is one of the points where Talend shines compared to, for example, Informatica. Informatica is designed to do one record at a time. It requires expert support and general competence in the product.

Talend, by default, can be very efficient, especially using the bulk load and bulk insert components, which, at the moment we are using. We are moving to approximately 10 terabytes of data daily. Notwithstanding the load, we had to tweak very, very little. Using standard components we could achieve our overall needs.

The fact that the technical support is out of China means that sometimes the engineers don't have a good command of the English language. That could hinder the overall experience. Apart from that, most of the incidents were resolved in 48 hours. Therefore, we're pretty satisfied with the level of service we've received.

I have previously worked with Informatica and TIBCO. I still believe Talent is superior. 

Obviously, being on AWS, we're using Linux AMI machines or vertical machines, using two machines. The setup was very easy. The only difficult part was to set up to the current time zone, however, this is nothing to do with Talend. We were having issues when Talend jobs were reporting the wrong date when they arrived because the set up was ETC rather than the local time zone.

Setting up Talend and setting up the administration console at the Tac server was very, very easy for somebody with a Linux System Administration skillset.

I set up the solution on my own.

I don't deal with corporate and pricing. I am just an IT Consultant. I honestly don't know the costs to run the solution. I don't know the price. I know people in the finance department are often complaining about the price, however, I don't know what the exact number is. 

It's all relative, after all. I have a very strong Oracle background and the Oracle price is totally outrageous. I don't believe that Talend prices are in the same ballpark as Oracle. I don't understand why people are complaining. That said, I don't deal with signing contracts and processes so I really don't know.

I am an IT Consultant. I use it currently in my job. I'm providing services to a company in Australia, using Talend.

I would advise others to use the Studio. If you have to pay for some license to use the key parallelize component, it's a good idea to do it. However, don't use the TAC. Use the other orchestration services like Control-M or AWS functions such as AWS Lambda. Don't use the TAC. The TAC is really ugly.

Overall, I'd rate the solution eight out of ten. I'd rate it higher, however, the TAC is unreliable. It's a big part of the solution, and, while I do really appreciate Talend Studio and the ability to link into a producer to make a Java code, which is ugly, I don't care because the job is done anyway. The fact that the orchestration is creating execution plans, from the TAC it's fine. However, when the running of the execution plan, sometimes there are issues. The job remains stuck on the actual server. I've had a lot of issues with TAC. 

Our primary use case is for data migration and validations.

This solution has helped our organization by allowing us to query from different sources and transform and send it to APIs through API calls.

The most valuable feature for me when it comes to this solution is that it's easy to use.

I would say that writing to JSON is kind of a pain. It reads from a JSON file pretty well, but writing to a JSON file is not so great because its components are not good. I would say this is the most important.

I have been using this solution for about six months.

I would rate the stability of this solution a nine, on a scale from one to 10, with one being the worst and 10 being the best.

I would rate the scalability of this solution an eight, on a scale from one to 10, with one being the worst and 10 being the best. There are around seven or eight users of this solution in our company. Eventually, we plan to scale to 20 people.

I would rate the technical support of this solution a nine, on a scale from one to 10, with one being the worst and 10 being the best.

Positive

I would say that the initial setup was medium-difficult.

I would recommend other people looking into this solution to pay attention to the learning curve and the documentation, which is the solution's strong suit. The Talend academy is a good place to start.

I would rate this solution as a whole a nine, on a scale from one to 10, with one being the worst and 10 being the best.

We have used the solution for a real estate agency in Singapore to stream their data on a more or less real-time basis to a mobile app. Their backend system is primarily built on SAP. They used a combination of Kafka message querying and Talend to stream the data into a NoSQL environment, which is MongoDB. The solution basically streams the data from SAP backend systems, all the way to a NoSQL MongoDB database, to support a real-time or near real-time data flow into a mobile app. 

This mobile app will be a consumer-facing app. The end consumers will be able to look at the status of their real estate space. Users are mostly the tenants who either rent or lease commercial or residential spaces. The status of their leased property will be made available via a mobile app. The data solution comprised of technology such as Kafka for message queuing, Talend for data flow streaming, and MongoDB for storing the data. That's one use case.

The second problem solved using Talend is to build the data lake for internal data analytics at a government organization, again based in Singapore. Their backend systems are primarily supported by Sybase databases. From the Sybase databases, selective data is brought into a staging area via Qlik Attunity, which is a real-time data synchronization tool that uses the change data capture mechanism. Once the data comes to the staging environment through Attunity, then Talend takes over. Talend pulls that data and moves it to Cloudera's big data solution, the big data platform. Then, Tableau is used for data analytics and data visualization. This solution is set up for internal data analytics within the government organization.

The tool offered essential connectors to connect to various data sources and our big data platform. Our data sources were SAP/ MS SQL and Sybase. The Hadoop/ hive connectors are used to connect to the Cloudera-based big data platform. The components available to loop and dynamically pass source/target connections helped us to stream data based on source tables' metadata. This helps us to onboard new data sources quickly, rather than building a custom data pipeline for each new data source.

The main differentiator that I have seen between Talend and other data integration tools is the ability to view the data pipeline in the form of a program/ code. The other tools hide the backend code behind the scene, however, Talend shows the backend code that gets generated from the UI (user interface) components used for creating a data pipeline. I.e., In most of the data integration tools, all we do is, leverage certain UI components meant for data processing such as reading, selection, filtering, sorting, writing et cetera to build data pipelines. The tools such as Pentaho or Informatica, will convert the pipeline into a backend code, which is written probably in C++ or java program. This is not transparent to the developer or the programmer. But in the case of Talend, the tool converts the pipeline into a programmatic format and shows it to the user. This helps in debugging errors. 

The json parsers can flatten the API response body into a structured output. This is useful when we try to use Googleapis for YouTube video analysis and to check corporate status uding ACRA/IRAS apis from Singapore governments.  

If somebody has a passion and interest in software programming, they will like this feature. Of course, we can do without it, however, this additional feature available in Talend helps the data engineer to understand the code better, understand how to better tune for performance, and so on. The differentiation is the ability to view the data pipeline in the form of a traditional software program.

Comparing the plus and minus of other tools and will try and suggest what can be improved in Talend based on how other tools implemented certain features. 

Both Talend and Pentaho leverage open-source plugins. There are lots of open-source committees that build solutions as per their requirement;  Say, for example, someone may have had a need to create a Tableau data extract from a certain database for the purpose of data visualization in Tableau. They may have created a plugin for this purpose and shared it with the market. We can always go into the market and search for a plugin that someone else created (for ex., to generate TDE files) when we have similar needs. Both Talend and Pentaho offer the 3rd party plugins in their market. This plugin market feature automatically extends/improves the tool capability. If somebody needs a particular feature, they can always build one and publish it for the other developers to use. 

Other than this, maybe if Talend had a few components, it's easier to deploy solutions; job scheduling is one. Currently, the job scheduler is a separate component within Nexus and is accessible over browser. It can be integrated within TOS (Talend Open Studio) so that we dont need to switch between the two. Nexus holds the repository of compiled program code. However, Nexus doesn't have the ability to keep the repository of the source code programs. That can be improved. 

Currently, Talend has a versioning feature, meaning the previous version can be named as 0.1 or 1.0 and the subsequent minor/major versions can be increased with incremental version numbers, however, it is not that great as a version control repository (such as VSS, CVS, Git, etc). If a Nexus-like tool can be used for maintaining versions of the underlying source code (not just for the compiled code), that would be great. Basically, version control can be improved.

I've been using the solution since 2019.

The stability of the solution is mainly based on the server architecture behind the scenes. We have seen some instability issues on other tools around the Talend platform. For ex., Qlik Attunity had been throwing some exceptions every now and then, however, in the case of Talend, we haven't seen many. At times the server would run out of memory. Based on the capacity we have, we may have to go and clean up a few logs and other systems’ data before resuming the processes manually. 

The system's stability is okay, especially in the case of our data warehouse. Users do understand that a data warehouse is less critical when compared to operational systems. The users' reports are normally generated at the end of the day for their availability, the next day. We have a workable level of stability, which is good enough. We don't see any instability issues.

Talend operates on a clustered job server setup, available in both Linux & windows. The clusters can be scaled up with additional nodes as per demand. In the case of an on-premise setup, we assess the load and define clusters based on the load. We did not have auto-scaling.

Talend has a support portal and we can get access to the support portal. The initial process could be a little difficult, to get into the support. The initial access provisioning could be improved. It took about a week's time to get a support login created. Once that is done, then you will get quality answers to the support questions.

There are two ways to get technical support, either from the dedicated support team from Talend, or from the open-source community. The dedicated team provides an answer for sure, however, we may not get answers to all our questions from the open-source forums.

Neutral

We are aware of the other solutions such as Pentaho. But, there was no switching. For most of the customers, I do the evaluation of tools, over one to two months and then finalize on one particular tool. They don't really move around from one ETL tool to another ETL tool, unless the tool itself is getting obsolete or if it is no longer supported. In the case of Talend, from what I have seen, there is no switching. They must have initially evaluated a few tools and finalized with one. The main reason could be that Talend supports a big data environment. Talend has the ability to integrate with market solutions. Third-party integration is possible. Talend is also becoming popular in Southeast Asia, so skilled resources are readily available in the market if we need people to maintain the environment. Those could be some of the factors that influence the selection of Talend.

Initial setup requires a systems engineer, who has knowledge in Linux/ Windows OS, depending on the server type, to work with Talend support. It takes about 2-3 weeks for the basic setup. For additional plugins/ components, guidance from Talend support team is required.

After the initial setup, most of the ETL data pipelines take about a week at the minimum to build. Typically, we reap the benefits after a month or two from a particular data stream. Of course, it is based on the different use cases and depends on the number of data pipelines involved in solving that particular use case, however, smaller scoped items can be delivered in one to three months' time. 

After development and testing, the time required for the deployment varies, depending on the process we adopt and depending on the version control tools that we have as well. Certain tools will easily integrate into the Talend environment. In those cases, I mean, it would be a medium-complexity deployment. We can't say it's very simple, we can't say it's too complex either. There is a medium level of difficulty involved in deployment.

The time it takes depends on the processes a particular organization follows in terms of change management and deployment. Some will require at least one week of review with the change management board. In certain organizations, the approval processes may take up to three weeks to get something deployed. If the process is a little simpler, if the developer has a fair level of control, it could be just one week.

A vendor team was in charge of the server maintenance and their scope of service included deployment as well, as developers do not have access to production networks in established firms. Developers normally provide a step by step instructions in a word document that the vendor team will follow. Some familiarity with the tool is enough, but the vendor personnel we worked with had the reasonable experience to an extent where they recommended code improvements. 

Typically before embarking on a project, we analyze the return on investment, which could be over two to three years. It could be as quick as three months, depending on the scope of the data integration project, however, in the case of a data warehousing solution, it could be two to three years. 

The real estate company we worked with, must have already seen the return on investment. Their mobile apps should be live with the data integrated at the backend. 

For the internal data analytics use case, they would've also seen the benefits, as the data is already available in the data lake. The users will be able to do the analysis with the integrated data pool in the data lake. 

Both the companies have seen the returns.

Pricing is competitive in comparison with Pentaho. Both are at par. Solutions such as Informatica could be more expensive. Certain packaged solutions that use Talend as ETL may be available, if you are looking for a pre-built data warehouse model.

Yes, Apache NiFi was evaluated. Based on the POC (proof of concept) results, we chose Talend.

Some of my comments are based on my limited understanding of the tool. Please do due diligence before selecting the tool. I recommend a POC over 1-2 months on shortlisted tools, before finalizing one.

The product is easy to install and configure. It is one of the best tools for data integration.

It is complicated to understand the configuration process for email components.

We have been using Talend Open Studio for two to three months.

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

I rate the product’s scalability a nine out of ten. Currently, we have one user in our organization. We plan to add more users in the future.

The initial setup is straightforward. It takes a couple of hours to complete.

It is an open-source product.

I rate Talend Open Studio a nine out of ten. It is an interesting tool to learn. It has many components compared to other products. It supports multiple operating systems and platforms.

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.

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.

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.