acho.io VS Apache Camel

acho.io Reviews

1. Jason    

   Data analyst at Comcast | about 3 years ago
   Great for accessing huge datasets

   I use Acho for storing and editing my data files. It's amazingly fast, and intuitive to use. The dashboard is still in beta but works pretty well with the data sync feature.

   👍 Pros:    Great customer support|Great user experience|Great set of functions

   👎 Cons:    Few features are in beta

Apache Camel Reviews

acho.io mentions (2)

• New Grad Tasked with Building a Data Pipeline

  The company I work at called Acho built a solution that combines ETL + DW + DMBS. If your data needs to be consumed by end production beyond SQL queries (BI, spreadsheets, reports, distribution...), it could be pretty powerful. It all depends on the production goal. If you simply want data on cloud, you probably wouldn't even need replication. Source: over 2 years ago

• What tool do you recommend for basic reporting (not visualization) from a cloud based DW? (Snowflake)

  I'd probably consider an online DB GUI like Acho for this. Not sure if they connect with Azure Blob directly. Then your stack can be BLOB landing --> Matillion 'ELT' --> Snowflake tables ---> versioned table for each team member on Acho ---> Extracts by end users (no SQL needed). Source: over 2 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 / 8 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: over 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