CloudAMQP VS Google Cloud Dataflow

CloudAMQP Reviews

Google Cloud Dataflow Reviews

CloudAMQP mentions (2)

• Architecture for processing thousands of images upon a single request

  RabbitMQ dude! Spin up a free instance on cloudamqp.com (not affiliated, but I use them in prod - free instances already are enough for many use cases), throw a bunch of consumers in the queue, push as many jobs as you want and you'll have an awesome indestructible working process. Source: about 2 years ago

• Parcel Tracking Application With RabbitMQ

  We can prefer to install RabbitMQ on our local machine but in that case, the installation steps would be different from the operating system to the operating system and we would need to mess with some network settings. Therefore, we make this step with http://cloudamqp.com. To do that let's create https://cloudamqp.com. Later on, click on the button Create New Instance and create a new message broker instance. We... - Source: dev.to / about 3 years ago

Google Cloud Dataflow mentions (14)

• How do you implement CDC in your organization

  Imo if you are using the cloud and not doing anything particularly fancy the native tooling is good enough. For AWS that is DMS (for RDBMS) and Kinesis/Lamba (for streams). Google has Data Fusion and Dataflow . Azure hasData Factory if you are unfortunate enough to have to use SQL Server or Azure. Imo the vendored tools and open source tools are more useful when you need to ingest data from SaaS platforms, and... Source: over 1 year ago

• Here’s a playlist of 7 hours of music I use to focus when I’m coding/developing. Post yours as well if you also have one!

  This sub is for Apache Beam and Google Cloud Dataflow as the sidebar suggests. Source: over 1 year ago

• How are view/listen counts rolled up on something like Spotify/YouTube?

  I am pretty sure they are using pub/sub with probably a Dataflow pipeline to process all that data. Source: over 1 year ago

• Best way to export several GCP datasets to AWS?

  You can run a Dataflow job that copies the data directly from BQ into S3, though you'll have to run a job per table. This can be somewhat expensive to do. Source: over 1 year ago

• Why we don’t use Spark

  It was clear we needed something that was built specifically for our big-data SaaS requirements. Dataflow was our first idea, as the service is fully managed, highly scalable, fairly reliable and has a unified model for streaming & batch workloads. Sadly, the cost of this service was quite large. Secondly, at that moment in time, the service only accepted Java implementations, of which we had little knowledge... - Source: dev.to / about 2 years ago