Infoworks.io VS Apache Camel

Infoworks.io Reviews

Apache Camel Reviews

Infoworks.io mentions (4)

• Dilemmas of getting production data into staging

  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: over 2 years ago

• Replicating data out of a production replica RDS DB into Redshift, options?

  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 3 years ago

• Fivetan vs. Stitch vs. Singer vs. Airbyte vs. Meltano

  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 3 years ago

• No-code data engineering solutions

  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 3 years ago

Apache Camel mentions (12)

• Ask HN: What is the correct way to deal with pipelines?

  "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 / 7 months ago

• Why messaging is much better than REST for inter-microservice communications

  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 / about 1 year ago

• Can I continuously write to a CSV file with a python script while a Java application is continuously reading from it?

  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: about 1 year ago

• S3 to S3 transform

  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 1 year ago

• 🗞️ We have just released our JBang! catalog 🛍️

  🐪 Apache Camel : Camel JBang, A JBang-based Camel app for easily running Camel routes. - Source: dev.to / over 1 year ago