Apache ActiveMQ VS Google Cloud Dataflow

Apache ActiveMQ Reviews

Google Cloud Dataflow Reviews

Apache ActiveMQ mentions (5)

• Top 6 message queues for distributed architectures

  Apache ActiveMQ is an open-source Java-based message queue that can be accessed by clients written in Javascript, C, C++, Python and .NET. There are two versions of ActiveMQ, the existing “classic” version and the next generation “Artemis” version, which is currently being worked on. - Source: dev.to / 12 months ago

• Data Engineering and DataOps: A Beginner's Guide to Building Data Solutions and Solving Real-World Challenges

  For real-time streaming, we have other frameworks and tools like Apache Kafka, ActiveMQ, and AWS Kinesis. - Source: dev.to / over 1 year ago

• Interview for JetBrains: Why Localazy developers ️ Kotlin?

  The back-end is designed as a set of microservices communicating through a message broker, ActiveMQ, with a custom configuration to support delayed delivery and other features. - Source: dev.to / almost 2 years ago

• Advice for real-time UDP over the internet

  My suggestion would be: don't try to reinvent the wheel. There are communications solutions out there already intended for this kind of use case, like https://activemq.apache.org/ (I point this out because Amazon MQ is based on ActiveMQ). Source: almost 2 years ago

• Sending message asynchronously (JSM)

  First we have to run a broker in my case I use activeMq You can download the file zip and after extract the file you can acces to the bin foler and run. - Source: dev.to / about 2 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 / almost 2 years ago