Qlik Talend Cloud Reviews

Our use case involves exchanging data in batch mode between applications, particularly in the retail sector. This includes interactions between the point of sales and the ERP system, both ways. 

Additionally, it covers the software for dealing with store replenishment, transforming various objects into flat files for now, and ingesting them in batch mode. We utilize webhooked jobs to be reactive and act as auxiliary support. This is our use case description.

The process of upgrading the software is quite easy. For instance, upgrading the Studio is straightforward, especially if done automatically. However, I typically do it manually by downloading the patch and placing it in the dedicated folder before restarting the studio. 

I have successfully requested the necessary patch from Talend support multiple times to align different studio versions across the team of developers. It was not difficult, and having access to Talend support directly from TNC proved quite beneficial. Our business has been running smoothly for three and a half years.

I understand this might relate more to another platform, like the cloud API cloud platform. Nevertheless, data management could also encompass APIs and real-time streaming data integration. I wonder if, at the same price, the API component could be added, which would be beneficial.

I have used the solution in this project for about two and a half years.

The solution is quite stable. We have not encountered many issues with remote engines, and the interfaces are properly developed. 

Most technical errors we face are caused either by development issues or third-party software applications to which we connect. 

Overall, the management and running environment are very stable, and I would rate it an eight out of ten.

Technical support is available and accessible.

Before Talend, I had some experience with SSIS for integrations. My expertise primarily started with Talend, though I did occasionally work with other tools like SSIS.

The deployment setup is not overly challenging. While I did not handle the deployment directly, with Talend Cloud or the management console, you can easily set up the environment and workspaces and install remote engines. Installing the Studio on virtual machines and connecting with SSO to TMC is straightforward.

The initial installation was handled by the infrastructure team on the customer side, which consisted of just a couple of individuals.

Overall, my advice is to consider this product as a strong option. 

I would rate the overall solution eight out of ten.

We were using Talend as a data warehouse for SecureSkilled Data related to a pension system. It acted as an SQL repository and was used for data warehousing and data governance, applying constraints on data before loading it into the warehouse.

We used Talend for ETL functionalities and to apply governance rules on some fields of data tables in our data warehouse.

The tool was mainly used for ETL processes to apply governance rules on data.

The biggest challenge with Talend was its performance. Sometimes data cleaning from the data warehouse was very slow, and we had to restart the server to enhance performance.

We used Talend for around two years, from 2021 till 2022.

Sometimes, our data cleaning process was very slow, requiring server restarts.

I did not contact Talend technical support.

Neutral

I also worked with Informatica, which I found to be better in terms of performance and cloud availability.

I was not involved in the deployment, but it took around two to three weeks.

It was managed internally by our resources.

Talend was an open-source tool, so there were no fees associated with it.

We were comparing Talend with Informatica, which I found to be more performant and provided features like dashboards for data quality.

I recommend Informatica over Talend due to Talend's performance issues.

Our primary use case involves integrating diverse data sources into our projects. These sources include data servers, fax files, CSV files, databases such as SQL and Postgres, and various other formats like Excel.

Talend's most valuable feature is its ability to generate code and packages efficiently. This feature streamlines the integration process, saving developers time and effort. Additionally, the stability of the generated code is noteworthy, as it ensures reliability over time. Despite not always producing the most aesthetically pleasing code, it eliminates critical errors, reducing the burden on developers. This stability is particularly crucial in complex integration scenarios, where errors can have significant consequences.

The product's setup process could be simpler.

We have been utilizing Talend Data integration for five years.

Our organization utilized Microsoft's SSIS for data integration before. However, we switched to Talend because of its simplicity and ease of use.

One key difference between Microsoft's SSIS and Talend data integration is their approach to integration. Talend emphasizes Java integration, which a robust Java assistant further supports. It provides its job ecosystem, which users utilize.

The initial setup was relatively straightforward, although it required careful attention to various components such as developer training, transformation models, and system configurations. Its versatility extends beyond simple data integration, offering powerful tools for backend processing and Java library integration. Challenges during implementation were mostly related to the complexity of the ecosystem and licensing issues, but these were manageable with appropriate expertise. While the setup may require effort, its robust features make it a valuable asset for organizations seeking efficient data processing solutions.

The product pricing is considered very good, especially compared to other data integration tools in the market.

In a previous role, I implemented Talend's integration solutions, providing installation and training to my team. It was vital for processing data in our databases and BI platform. For instance, it efficiently handled file reception from clients, identifying errors and integrating data seamlessly. This streamlined approach improved efficiency, especially with a substantial increase in processing volumes to 38,000 batches.

I recommend the product to others and rate it a ten out of ten.

The effectiveness of the Talend Data Management Platform varies depending on specific use cases. For instance, it integrates customer data from CRM systems, ensuring cleanliness. Additionally, it facilitates the inclusion of accounting information, thereby connecting both datasets seamlessly

The solution is connected to various phones. It retrieves the configuration from the system.

The solution's stability could be improved.

I have used the Talend Data Management Platform for ten years.

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

Ten people are using this product. The solution is scalable. It depends on how much scalability and agility you want in the system. Scaling is much easier with added security.  I rate the solution’s scalability a nine out of ten.

For deployment, the support was invaluable. A team of 25 members collaborated closely with the tech team to assist them in decision-making. It took a week to deploy the solution.

The product is cost-effective. If you have to do it with Talend or any other informational tools, it's very expensive. It has a very flexible licensing cost. It's a SaaS-based model. It costs around 20,000 bucks. Compared to other ETL tools, it's much more cost-effective and flexible. It's tailored to the customer's needs. They also have data management and solid data suites within their system, not just file management.

The APM is similar, and they have certain tools in Talend, such as scheduling, that provide real-time data. Talend can be complex, but it presents a challenge. The version is much simpler and easier to use. Additionally, it allows non-technical users to access the system, saving resource costs and reducing time wasted on the data platform. 

Each one of them has their particular functions. Informatica and Talend have their specific details, which are good. The current UI of Talend and interfaces is good. It's priced at 30,000. Even though it is a startup, Talend's data suite is more promising and they are more agile.

Dell Data Suite is a part of the package that provides compliance and establishing a relationship.

The file management system is part of it. If you want to use it entirely, that's a different package. If you're looking at ETL, you can use the file management system as a staging area, where the cost is a little higher on the second side. More focus is on data transformation, the overall process, and compliance. Other ETL tools cost between fifteen and twenty thousand dollars, but Talend's data suite is a fraction of that price.

Overall, I rate the solution an eight out of ten.

We use the product to collect and report data to the Power BI dashboard. 

The product's integration with PostgreSQL and Jira has been helpful for us. Its performance is good. However, we do not use it for large data sets. 

Due to using the open-source version of Talend Data Integration, which lacks a scheduler, our current approach involves developing jobs in Talend, exporting them as Java packages, and utilizing an external scheduler, such as Windows Scheduler, to manage the scheduling process.

I have been using the product for nine months. 

The product's stability is good. 

We have no support since we use the open-source version. 

I have used Informatica before Talend Data Integration. 

The tool's deployment time varies based on the development scope. Smaller deliverables may take half a day in an agile environment, while larger deployments could exceed several hours. On average, deploying one job takes around two to three hours. We may require three resources to handle the deployment. 

I have been using the open-source version. 

The tool's learning curve for new users is good. I rate the product an eight out of ten. Before using Talend Data Integration, it's important to remember that it requires effort in data development. There are numerous configurations to handle, and the deployment process can be lengthy, depending on the specific version in use.

We use Talend for the ETL tool data integration. We're using Talend with Spark to capture large volumes of data from multiple sources and load it to the data lake. We're using version 12.

We deploy it in our organization and to our client through AWS as a cloud provider.

We have one IT consultant and 180 people in different technologies, particularly in the data integration side. At least 50% of them know Talend, and some of them know Ab Initio or Informatica.

We may increase usage, but there are more tools coming up in this space, like Kafka real-time integration. Other data integration capabilities are coming up.

This solution has helped us extract data from various sources and load it into the data lake for our client as a large regional bank.

The most valuable feature is the data loading and scripting language. Talend graphs are more user-friendly for developing, modifying, and embedding in business logic.

There are some glitches, but mostly they'll fix the ongoing feedback we give to the product guys. However, there could be more enhancements. They're bringing deduplication capabilities to Talend. 

I think they should drive toward AI and machine learning. They could include a machine-learning algorithm for the deduplication.

5 Years

It's stable.

It's scalable.

Technical support is average. I would rate them 3.5 out of 5.

Positive

IBM DatStage, Informatica, and Ab Initio, modern technology is the reason I switched

Installation is straightforward. Deployment only takes a couple of days – maybe a day or two with the infrastructure side. For implementation, you have to write a code in order to get the data.

Deployment can be done in-house if you have dealt with a lot of ETL tools that are integration tools.

50% savings in data integration capabilities

The price is on a per-user basis. It's a little more expensive than other tools. There aren't any additional costs beyond the standard licensing fee.

The licensing compared with IBM tools is like 50%.

We evaluated Informatica and Ab Initio. We chose Talend because of the data capabilities. It's a better tool for our requirements.

I would rate this solution 8 out of 10.

We are currently using it for data integration and API application integrations. The integrations are used for sourcing the data from various sources. We're getting it into one data platform.

The availability of connectors is great.

The data integrations on offer are quite useful. 

There's a stitch data loader that has proven to be helpful. 

Technical support is helpful.

It has a pretty straightforward setup, depending on the environment. 

Scalability isn't an issue.

It's lacking on the change data capture side. When we go into projects of that nature, we move over to other vendors to do the job. It would be helpful if they were stronger here. 

I'd be interested in seeing the running of Python programs and transformations from within the studio itself. Right now, we have to call it from the CLI. We'd love to use it in the same way we use Java, with more simple copy-paste functionality.

I've used the solution for six or seven years. 

The stability does depend on the features. Some features are not as stable as they could be, and some are not backward compatible. If there is some mismatch, it can break. You do have to update everything separately, and it is important to update from the same source.

It all comes down to how you set up everything. 

Some features are really stable. Some features are not backward compatible. One of the issues that I am currently facing is making sure that the API pipelines that we have created are version compatible with the run time server that we have installed. Ffrom a readability point of view, if you have to upgrade each and every thing separately, it's hard. There is a little bit of room for improvement when it comes to upgrading from the same source. That said, it depends on how you are setting up your environment.

We currently have the data integration environment and the remote engines and everything set up so that our upgrades happen using just one script. For Runtime, that is not yet done. This is something which we are doing currently. So stability totally depends on the way you configure it. Of course, there is room for improvement from the Talend side as well.

The solution is scalable. It is platform-independent.  Scaling depends on the person providing the infrastructure. If we've provisioned properly, there are no particular limitations. 

In one project, we have 40 developer users and another 15 people in stewardship positions. 

We contact support frequently, and they are great. I haven't had a bad experience yet. 

We have used other vendors. Currently, there are two types of vendors you can see on Gartner: those that are cloud-based and some that are hybrid. Talend is a hybrid tool. As an overall data fabric solution, Talend is leading the market. It used to be Informatica. However, their cloud is not yet that mature. 

When it comes to cloud integrations, Talend has competition from Azure Stack. While not that mature, it is really competing with Talend head-to-head and has a lot of great applications. 

Half of my clients prefer Talend, and the other half go to Azure. 

Depending on how you want to manage the project, it's pretty easy to set up. A simple spin-up is quite fast, and you can use it right away. However, it offers CI/CD pipeline compatibilities, and that process might take longer. 

The pricing is moderate. It's not too high or low. If you want a small setup with five or six users, Talend is a good option and comes quite cheap. It's a great way to enter into this area of technology.

I'd rate the solution eight out of ten. 

We are Talend platinum partners. 

Our company uses the solution to provide data integration services for customers. Most of our implementations are on-premises for large or enterprise-level customers. 

We have six users with experience in both the local studio and the enterprise versions. 

The solution can run on any machine and that is a big advantage. 

The big data component allows us to do VELTPs. 

The solution is packed with features. 

There are some limitations on the monitoring side so support is not minimal when compared to Informatica. 

The solution's memory sometimes bottlenecks and that can be challenging, even for technical support. For example, we sometimes have issues with loading 16GB files. 

The logging and scheduling sides could improve. 

I have been using the solution on and off since 2007. 

The stability is rated an eight out of ten. 

The solution has great, dynamic scalability. You just put it on the cloud and run it with no issues. 

Technical support sometimes struggles to solve memory bottlenecks. 

The setup is moderate but not too complex. The implementation is more complex because you have to configure everything.

We implement the solution for customers. The implementation time depends on the client and project. 

A large-scale implementation with different XMLs, different key messaging queues, and big data takes six months to a year. 

Customers realize ROI because the solution saves time and resources. 

The solution's pricing is very reasonable and half the cost of Informatica. 

The solution sometimes has memory bottlenecks when processing big files. Other products such as Informatica load files very easily. 

Informatica is built for ETL and has more functionality tied to that mode, but is twice the price of the solution. 

The solution is built for everything including ELP, ETL, and data or application migrations. 

I recommend the solution because it is customizable and flexible. I rate it a seven out of ten. 

The solution is based on Java. It connects to all available data sources, like APIs, Workday, Salesforce, relational database management systems, Azure, Google Cloud, and AWS. It can do big data processing. It also does batch processing and streaming. It hosts APIs, too. We can consume the queuing mechanisms like Kafka or Java Message Queue.

We migrated from JD Edwards to SAP. It could have been a very tough transition. However, with the help of Talend, we could do it smoothly. It provided us with connectors that made our job easy.

We can develop our own code if we do not see the functionality we need. We can write our own code and call it in the integration pipeline. It is the greatest feature. Once we build JAR, we can run it anywhere we want. We do not need Talend to run it. We can use any third-party scheduler to schedule the job and do a performance check.

The vendor successfully created a cloud solution. However, lifting and shifting all the functionality available on-premises will be a heavy task. They are working on it. The product must enhance the data quality. Data lineage features must be integrated seamlessly into the data integration platform.

I have been using the solution for more than eight years.

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

I rate the tool’s scalability a ten out of ten. We can scale it however we want. It's very flexible.

We used DataStage and Informatica. We switched to Talend because of its price. It also has a wide range of functionality bundled together. While using Informatica, we had to buy everything separately. DataStage and Informatica charge premium prices. It costs us around 25,000 per license.

The solution is deployed on the cloud. The initial setup is fairly straightforward and self-explanatory.

We have seen a return on investment. The solution is easy to deploy. We can deploy it on the JVM servers. We don't need any specific servers to execute the pipelines. People could save a lot of money if they use the tool.

The tool is cheap.

We evaluated Airflow. Talend was a better choice.

It's a fairly self-explanatory tool. We get a lot of advice from the community. People must register with the community. It will help them get started very quickly. Overall, I rate the product a nine out of ten.

We are using the Talend Data Management Platform development.

The solution can be deployed on the cloud or on-premise.

It is easy to create job opportunities within an organization by utilizing data from external sources, which enriches the company's data when connecting to other platforms. Similarly, importing data into your company is a straightforward process. Compared to other solutions, the Talend Data Management Platform makes developing jobs easier.

The most valuable features of the Talend Data Management Platform are the components.

The sales and market department could improve the Talend Data Management Platform.

I have been using the Talend Data Management Platform for approximately six years.

The stability of the solution is excellent.

The scalability of the Talend Data Management Platform is good. It has load balancing and failover features.

We do not have plans to use this solution this year but next year we will increase our usage.

We have four people who use the solution.

Local support from the Talend Data Management Platform can be in Portuguese and sometimes they do not have a resolution. The support can be in different countries but we have a resolution most of the time in Brazil.

The initial setup of the Talend Data Management Platform is of a medium difficulty level.

After two years we break even for the costs of the solution.

The price of the Talend Data Management Platform is reasonable. The other competing solutions are priced high. Gartner Magic Quadrant identified other solutions, such as Informatica, that are far more expensive.

This solution delivers quick development.

I rate Talend Data Management Platform an eight out of ten.