Infoworks eliminates big data complexity by automating data engineering through the company’s Autonomous Data Engine, which has been adopted by some of the largest enterprises in the world. Using a code-free environment, Infoworks allows organizations to quickly create and manage data use cases from source to consumption. Customers deploy projects to production within days, dramatically increasing analytics agility and time to value.
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Based on our record, Apache Camel should be more popular than Infoworks.io. It has been mentiond 13 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
You should check out infoworks.io - they have this concept of domains which can restrict data sets and the users that can do any transformations on it. They have a full airflow based visual orchestration engine as well as scheduler, transformation engine, ingestion, cataloging, etc. It's an end to end unified data engineering product. Source: almost 4 years ago
For a simpler no-code visual config-driven (data ingest+ ELT+ airflow-based orchestration), all in a single unified platform, you may consider infoworks.io. It will even auto create a metadata catalog for you and give you lineage, audit capabilities. Source: almost 4 years ago
As long as you're truly after a lo/no-code solution that can automate your data onboarding (beyond ingestion), you'd be amiss to not try infoworks.io. Source: almost 4 years ago
I'm alerted to another vendor, infoworks.io, that offers a unified data engineering solution. I took their free personal testdrive. I learned that they have large number of source connectors (I think I read 200+), Spark based transformation engine, and visual workflow based on airflow. Source: almost 4 years ago
Seamless integration of AML and KYC solutions with existing systems is critical for effective automation. Use middleware platforms like MuleSoft (commercial) or Apache Camel (open source) to facilitate data exchange or deeper integrations between many disparate systems. Integration testing to ensure faithful and ongoing interoperability between both proprietary and 3rd-party systems should be rigorous and will... - Source: dev.to / 10 months ago
"correct" is a value judgement that depends on lots of different things. Only you can decide which tool is correct. Here are some ideas: - https://camel.apache.org/ - https://www.windmill.dev/ Your idea about a queue (in redis, or postgres, or sqlite, etc) is also totally valid. These off-the-shelf tools I listed probably wouldn't give you a huge advantage IMO. - Source: Hacker News / over 1 year ago
This reminds me more of Apache Camel[0] than other things it's being compared to. > The process initiator puts a message on a queue, and another processor picks that up (probably on a different service, on a different host, and in different code base) - does some processing, and puts its (intermediate) result on another queue This is almost exactly the definition of message routing (ie: Camel). I'm a bit doubtful... - Source: Hacker News / over 2 years ago
Since you're writing a Java app to consume this, I highly recommend Apache Camel to do the consuming of messages for it. You can trivially aim it at file systems, message queues, databases, web services and all manner of other sources to grab your data for you, and you can change your mind about what that source is, without having to rewrite most of your client code. Source: over 2 years ago
For a simple sequential Pipeline, my goto would be Apache Camel. As soon as you want complexity its either Apache Nifi or a micro service architecture. Source: over 2 years ago
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