We performed a comparison between Apache Flink and Informatica Data Engineering Streaming based on real PeerSpot user reviews.
Find out what your peers are saying about Amazon Web Services (AWS), Databricks, Microsoft and others in Streaming Analytics."The top feature of Apache Flink is its low latency for fast, real-time data. Another great feature is the real-time indicators and alerts which make a big difference when it comes to data processing and analysis."
"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."
"Apache Flink's best feature is its data streaming tool."
"Another feature is how Flink handles its radiuses. It has something called the checkpointing concept. You're dealing with billions and billions of requests, so your system is going to fail in large storage systems. Flink handles this by using the concept of checkpointing and savepointing, where they write the aggregated state into some separate storage. So in case of failure, you can basically recall from that state and come back."
"Easy to deploy and manage."
"Apache Flink is meant for low latency applications. You take one event opposite if you want to maintain a certain state. When another event comes and you want to associate those events together, in-memory state management was a key feature for us."
"The documentation is very good."
"It improves the performance."
"In a future release, they could improve on making the error descriptions more clear."
"The solution could be more user-friendly."
"The machine learning library is not very flexible."
"Apache Flink should improve its data capability and data migration."
"There is room for improvement in the initial setup process."
"In terms of improvement, there should be better reporting. You can integrate with reporting solutions but Flink doesn't offer it themselves."
"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."
"We have a machine learning team that works with Python, but Apache Flink does not have full support for the language."
"Skill requirement is required. There is a learning curve."
Earn 20 points
Apache Flink is ranked 5th in Streaming Analytics with 15 reviews while Informatica Data Engineering Streaming is ranked 15th in Streaming Analytics with 1 review. Apache Flink is rated 7.6, while Informatica Data Engineering Streaming is rated 8.0. 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 Informatica Data Engineering Streaming writes "Helps with real-time data processing and improves decision-making overall". Apache Flink is most compared with Spring Cloud Data Flow, Amazon Kinesis, Databricks, Azure Stream Analytics and Amazon MSK, whereas Informatica Data Engineering Streaming is most compared with Google Cloud Dataflow, Starburst Enterprise, Databricks, Mule Anypoint Platform and IBM InfoSphere DataStage.
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