Apache Flink vs. Tealium Customer Data Hub

In well-suited scenarios, I would recommend using Apache Flink when you need to perform real-time analytics on streaming data, such as monitoring user activities, analyzing IoT device data, or processing financial transactions in real-time. It is also a good choice in scenarios where fault tolerance and consistency are crucial. I would not recommend it for simple batch processing pipelines or for teams that aren't experienced, as it might be overkill, and the steep learning curve may not justify the investment.

Incentivized

Tealium Customer Data Hub is great for situations where you want to collect data from a front end data layer and then route it to multiple data tools, or if you need the ability to transform the values collected before sending. There is a tremendous amount of customizability. It has also been good for tag management of marketing/advertising tags/pixels, but could use a little improvement with regards to putting many tags on the same page. If your situation requires a lot of complexity to the marketing tags, it is still very possible to do with Tealium Customer Data Hub, but could be less complicated. Luckily, Tealium Customer Data Hub's support crew is excellent and really will partner with us and help us succeed.

Incentivized

• Low latency Stream Processing, enabling real-time analytics
• Scalability, due its great parallel capabilities
• Stateful Processing, providing several built-in fault tolerance systems
• Flexibility, supporting both batch and stream processing

Incentivized

• Simple tag management that is tough to beat. So many solutions that are incredibly simple to setup and gather data for.
• Security around the data is key and Tealium excels in this area.
• The speed impact of the tag setup is key to optimizing and allowing our web properties to run more effectively, which is a better experience for the end user.

Incentivized

• Python/SQL API, since both are relatively new, still misses a few features in comparison with the Java/Scala option
• Steep Learning Curve, it's documentation could be improved to something more user-friendly, and it could also discuss more theoretical concepts than just coding
• Community smaller than other frameworks

Incentivized

• Tealium Customer Data Hub is powerful, but it has a significant learning curve. Users with JavaScript experience, developers (with a solid understanding of browser Dev Tools), and technical minded people will learn it more quickly.
• Some of the documentation seems lacking. My biggest complaint is that the documentation may explain things, but often is missing clear examples. If I had some clear examples, I could possibly avoid opening tickets for tech support.

Tealium continues to impress us with their focus on innovation and continuous improvement. Their support team makes use feel as though we are their one and only client. They exceed our expectations from both a product and people perspective, so we have no reason to look elsewhere!

Tealium iQ Tag Management System does exactly what it is intended for, it manages vendortags. Changes can be made to websites and apps in minutes. The frontend is well structured, updates are easy to carry out, and Tealium support is available at all times.

Incentivized

It's been flawless as far as I am concerned.

Incentivized

Great user interface. Easy to use. Very responsive.

Incentivized

Support team has always been great at addressing issues or questions, by providing answer or escalating it internally to the right individual. reply response time has been always reasonable. Some responses are responded with documentation doc but in some instances the question require a non-generic answer that can create a back-and-forth conversation.

Incentivized

Did what we needed to onboard us onto the platform

Incentivized

Implementation had some bumps in the road and it was new for all of us, but for the most part, it was easier than many other implementations we've done with other technologies.

Incentivized

Apache Spark is more user-friendly and features higher-level APIs. However, it was initially built for batch processing and only more recently gained streaming capabilities. In contrast, Apache Flink processes streaming data natively. Therefore, in terms of low latency and fault tolerance, Apache Flink takes the lead. However, Spark has a larger community and a decidedly lower learning curve.

Incentivized

Tealium Customer Data Hub can use 1P IDs and that is the main reason we selected it. with hindsight it was a good choice in this respect Tealium Customer Data Hub can process and forward event data via api, which AAM cannot AAM connectors can be set up with a few clicks whereas Tealium Customer Data Hub connectors require support from an engineer aam machine learning tools infer a score after every event so can be used for onsite single session use cases, whereas Tealium Customer Data Hub ML infers at end of session, so is only really useful for paid media / retargeting use cases Tealium Customer Data Hub's visitor stitching approach is broad brush and irreversible; AAM allows you to merge customer profiles at your discretion depending on the use case

Like anything it could be cheaper but we still feel we get value from it.

Incentivized

Never had an issue, scales as we use it.

Incentivized

Very easy to work with and relatively cost effective

Incentivized

• Allowed for real-time data recovery, adding significant value to the busines
• Enabled us to create new internal tools that we couldn't find in the market, becoming a strategic asset for the business
• Enhanced the overall technical capability of the team

Incentivized

• There has been a near immeasurable return on customer data and improvement of our quality for our physical products due to be in tune with the customer. This has changed our way of doing things for the better to gain a better flow and overall workplace experience.
• A negative is that Tealium AudienceStream becomes harder to manuever and use data analytics for when a database has been existing for a fairly large amount of time. It goes from an agile ship to a huge vessel that takes many components to be able to move.

Incentivized