We performed a comparison between AWS Glue and TIBCO Spotfire based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."It is a stable and scalable solution."
"The solution integrates well with other AWS products or services."
"The most valuable feature of AWS Glue is its ease of use and good documentation. Additionally, we can do all the transformations that we need."
"I also like that you can add custom libraries like JAR files and use them. So, the ability to use a fast processing engine and embed basic jobs easily are significant advantages."
"AWS Glue is quite better than other tools, but you have to learn it properly before you start using it."
"The solution's technical support is good. Whenever we raise a use case where we face an issue in our company, we get a response from the solution's technical team."
"I like the fact that AWS Glue works with Python scripts."
"AWS Glue is a stable and easy-to-use solution."
"It allows users to quickly analyze data from a variety of sources and visualize it with powerful, interactive graphs, and charts."
"The ability to connect to many different data sources is one of the key features. The other would then be the different ways in which that data can be visualized."
"We particularly like the data angling feature of this solution. This gives us the ability to work on data transformations, join files, and carry out other data preparation tasks all in a single tool."
"R and automation services."
"I appreciate Spotfire's range of visualization options, advanced analytics features, and seamless integration with other TIBCO products."
"The most valuable feature is the map visuals that help us connect to the geo-specialized data which is more advanced than other solutions."
"The ability to create a real-time data mark, using just one piece of software, is the best feature of this product."
"From a scalability standpoint, I would say it's pretty fantastic."
"The price of the solution could improve."
"It is not clear how the partition discovery would have been affected by more data coming in."
"The setup and installation is a bit complex without advanced knowledge or training."
"I haven't looked into Glue in terms of seeking out flaws. I've not come across missing features."
"It would be better if it were more user-friendly. The interesting thing we found is that it was a little strange at the beginning. The way Glue works is not very straightforward. After trying different things, for example, we used just the console to create jobs. Then we realized that things were not working as expected. After researching and learning more, we realized that even though the console creates the script for the ETL processes, you need to modify or write your own script in Spark to do everything you want it to do. For example, we are pulling data from our source database and our application database, which is in Aurora. From there, we are doing the ETL to transform the data and write the results into Redshift. But what was surprising is that it's almost like whatever you want to do, you can do it with Glue because you have the option to put together your own script. Even though there are many functionalities and many connections, you have the opportunity to write your own queries to do whatever transformations you need to do. It's a little deceiving that some options are supposed to work in a certain way when you set them up in the console, but then they are not exactly working the right way or not as expected. It would be better if they provided more examples and more documentation on options."
"If there's a cluster-related configuration, we have to make worker notes, which is quite a headache when processing a large amount of data."
"In terms of performance, if they can further optimize the execution time for serverless jobs, it would be a welcome improvement."
"I would like to see a more robust interface on the no-code side. This would be nice to be able to split cells."
"The initial setup of TIBCO Spotfire is in the middle range of difficulty. The initial setup of Power BI is easier."
"The handling and consumption of realtime data could be improved."
"The data compression has room for improvement."
"We would like to see some improvement in the default properties of the solution, so that there is less need for us to spend our time coding."
"We encountered difficulties connecting the special data sets, as the post data set did not contain any shared columns, making it difficult to establish a connection between the data sets."
"The design of the UI could be improved."
"Print capability and trigger-based events."
"When you do the data loading, it is slow."
AWS Glue is ranked 1st in Cloud Data Integration with 37 reviews while TIBCO Spotfire is ranked 13th in BI (Business Intelligence) Tools with 65 reviews. AWS Glue is rated 7.8, while TIBCO Spotfire is rated 8.2. The top reviewer of AWS Glue writes "Provides serverless mechanism, easy data transformation and automated infrastructure management". On the other hand, the top reviewer of TIBCO Spotfire writes "A robust BI tool, with good dashboard features and adverse event tracking". AWS Glue is most compared with AWS Database Migration Service, Informatica PowerCenter, SSIS, Informatica Cloud Data Integration and Talend Open Studio, whereas TIBCO Spotfire is most compared with Tableau, Microsoft Power BI, QlikView, Qlik Sense and Amazon QuickSight. See our AWS Glue vs. TIBCO Spotfire report.
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