Apache Camel Reviews

Presto DB Reviews

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 / 9 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 / over 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

Presto DB mentions (6)

• Parsing logs from multiple data sources with Ahana and Cube

  Presto is an open-source distributed SQL query engine, originally developed at Facebook, now hosted under the Linux Foundation. It connects to multiple databases or other data sources (for example, Amazon S3). We can use a Presto cluster as a single compute engine for an entire data lake. - Source: dev.to / about 2 years ago

• Can a data warehouse be skipped?

  Fair point, but I am talking about Athena (not SQL Server), which under the hood uses a distributed query engine. It is capable to deal with huge amounts of data, if the storage is in the right shape. You can read more about the underlying technology here: https://prestodb.io/. Source: about 2 years ago

• why use Redshift if we can use S3 to store data and can connect with Quicksight for dashboarding?

  So there is Presto, which is a distributed SQL engine created by Facebook. Source: over 2 years ago

• Understanding AWS Athena 101

  You can use Athena to run data analytics, with just standard SQL (Presto). - Source: dev.to / almost 3 years ago

• ETL tool for query building across multiple databases in Mongo DB

  Presto does this, but I'm honestly uncertain how performant it is. In my experience, centralizing data is the superior approach to attempting to query multiple sources in place. Source: almost 3 years ago