We performed a comparison between Apache Flink and PubSub+ Event Broker based on real PeerSpot user reviews.
Find out in this report how the two Streaming Analytics solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The product helps us to create both simple and complex data processing tasks. Over time, it has facilitated integration and navigation across multiple data sources tailored to each client's needs. We use Apache Flink to control our clients' installations."
"The setup was not too difficult."
"It provides us the flexibility to deploy it on any cluster without being constrained by cloud-based limitations."
"Easy to deploy and manage."
"With Flink, it provides out-of-the-box checkpointing and state management. It helps us in that way. When Storm used to restart, sometimes we would lose messages. With Flink, it provides guaranteed message processing, which helped us. It also helped us with maintenance or restarts."
"The documentation is very good."
"The event processing function is the most useful or the most used function. The filter function and the mapping function are also very useful because we have a lot of data to transform. For example, we store a lot of information about a person, and when we want to retrieve this person's details, we need all the details. In the map function, we can actually map all persons based on their age group. That's why the mapping function is very useful. We can really get a lot of events, and then we keep on doing what we need to do."
"Apache Flink's best feature is its data streaming tool."
"The most useful features has been the WAN optimization and probably the HybridEdge, which requires some third-party adapters or plugins. The idea that we can position Solace as a protocol-agnostic message transport fabric is key to our company having all manners of asynchronous messaging protocols from MQ, Kafka, JMS, etc. I really like the WAN optimization: Send once over a WAN, then distribute locally as many times as there are subscribers."
"The topic hierarchy is pretty flexible. Once you have the subject defined just about anybody who knows Java can come onboard. The APIs are all there."
"This solution reduces the latency to access changes in real-time and the effort required to onboard a new subscriber. It also reduces the maintenance of each of those interfaces because now the publisher and subscribers are decoupled. Event Broker handles all the communication and engagement. We can just push one update, then we don't have to know who is consuming it and what's happening to that publication downstream. It's all done by the broker, which is a huge benefit of using Event Broker."
"Going from something where we had outages and capacity issues constantly to a system that was able to scale with the massive market data and messaging spikes that happened during the initial stages of the COVID crisis in March, we were able to scale with 40 plus percent growth in our platform over the course of days."
"When we went to add another installation in our private cloud, it was easy. We received support from Solace and the install was seamless with no issues."
"The event portal and the diversity of deployment options in a hybrid landscape are the most valuable features."
"We like the seamless flexibility in protocol exchange offering without writing a code."
"As of now, the most valuable aspects are the topic-based subscription and the fanout exchange that we are using."
"One way to improve Flink would be to enhance integration between different ecosystems. For example, there could be more integration with other big data vendors and platforms similar in scope to how Apache Flink works with Cloudera. Apache Flink is a part of the same ecosystem as Cloudera, and for batch processing it's actually very useful but for real-time processing there could be more development with regards to the big data capabilities amongst the various ecosystems out there."
"The machine learning library is not very flexible."
"The TimeWindow feature is a bit tricky. The timing of the content and the windowing is a bit changed in 1.11. They have introduced watermarks. A watermark is basically associating every data with a timestamp. The timestamp could be anything, and we can provide the timestamp. So, whenever I receive a tweet, I can actually assign a timestamp, like what time did I get that tweet. The watermark helps us to uniquely identify the data. Watermarks are tricky if you use multiple events in the pipeline. For example, you have three resources from different locations, and you want to combine all those inputs and also perform some kind of logic. When you have more than one input screen and you want to collect all the information together, you have to apply TimeWindow all. That means that all the events from the upstream or from the up sources should be in that TimeWindow, and they were coming back. Internally, it is a batch of events that may be getting collected every five minutes or whatever timing is given. Sometimes, the use case for TimeWindow is a bit tricky. It depends on the application as well as on how people have given this TimeWindow. This kind of documentation is not updated. Even the test case documentation is a bit wrong. It doesn't work. Flink has updated the version of Apache Flink, but they have not updated the testing documentation. Therefore, I have to manually understand it. We have also been exploring failure handling. I was looking into changelogs for which they have posted the future plans and what are they going to deliver. We have two concerns regarding this, which have been noted down. I hope in the future that they will provide this functionality. Integration of Apache Flink with other metric services or failure handling data tools needs some kind of update or its in-depth knowledge is required in the documentation. We have a use case where we want to actually analyze or get analytics about how much data we process and how many failures we have. For that, we need to use Tomcat, which is an analytics tool for implementing counters. We can manage reports in the analyzer. This kind of integration is pretty much straightforward. They say that people must be well familiar with all the things before using this type of integration. They have given this complete file, which you can update, but it took some time. There is a learning curve with it, which consumed a lot of time. It is evolving to a newer version, but the documentation is not demonstrating that update. The documentation is not well incorporated. Hopefully, these things will get resolved now that they are implementing it. Failure is another area where it is a bit rigid or not that flexible. We never use this for scaling because complexity is very high in case of a failure. Processing and providing the scaled data back to Apache Flink is a bit challenging. They have this concept of offsetting, which could be simplified."
"We have a machine learning team that works with Python, but Apache Flink does not have full support for the language."
"There is room for improvement in the initial setup process."
"Apache Flink should improve its data capability and data migration."
"In terms of stability with Flink, it is something that you have to deal with every time. Stability is the number one problem that we have seen with Flink, and it really depends on the kind of problem that you're trying to solve."
"Amazon's CloudFormation templates don't allow for direct deployment in the private subnet."
"The licensing and the cost are the major pitfalls."
"Some of the feature's gaps with some of the open-source vendors have been closed in a lot of ways. Being more agile and addressing those earlier could be an area for improvement."
"A challenge we currently have is Solace's ability to integrate with single sign-on in our Active Directory and other single sign-on tools and platforms that any company would have. It's important for the platforms to work. Typically, they support only LDAP-based connectivity to our SQL Servers."
"We have requested to be able to get into the payload to do dynamic topic hierarchy building. A current workaround is using the message's header, where the business data can be put into this header and be used for a dynamic topic lookup. I want to see this in action when there are a couple of hundred cases live. E.g., how does it perform? From an administration perspective, is the ease of use there?"
"The integrations could improve in PubSub+ Event Broker."
"The deployment process is complex."
"The section on observability pertains to understanding the functioning of an event crash. Instead of focusing on how the crash occurs, attention is given to the observable aspects, such as a memory pipeline where one person pushes messages and another reads them. However, this pipeline often encounters issues, such as the reader being unavailable, causing the system to become stuck and preventing the messages from moving forward. This can lead to the pipeline being permanently stalled."
"The ease of management could be approved. The GUI is very good, but to configure and manage these devices programmatically in the software version is not easy. For example, if I would like to spin up a new software broker, then I could in theory use the API, but it would require a considerable amount of development effort to do so. There should be a tool, or something that Solace supports, that we could use for this, e.g., a platform like Terraform where we could use infrastructure as code to configure our source appliances."
Apache Flink is ranked 5th in Streaming Analytics with 15 reviews while PubSub+ Event Broker is ranked 10th in Streaming Analytics with 15 reviews. Apache Flink is rated 7.6, while PubSub+ Event Broker is rated 8.6. The top reviewer of Apache Flink writes "A great solution with an intricate system and allows for batch data processing". On the other hand, the top reviewer of PubSub+ Event Broker writes "Event life cycle management changes the way a designer or architect will design a topic and discover what is available". Apache Flink is most compared with Amazon Kinesis, Spring Cloud Data Flow, Databricks, Azure Stream Analytics and SAS Event Stream Processing, whereas PubSub+ Event Broker is most compared with Apache Kafka, IBM MQ, VMware RabbitMQ, ActiveMQ and Confluent. See our Apache Flink vs. PubSub+ Event Broker report.
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