NATS VS Google Cloud Dataflow

NATS Reviews

Google Cloud Dataflow Reviews

NATS mentions (63)

• Implementing OTel Trace Context Propagation Through Message Brokers with Go

  Several message brokers, such as NATS and database queues, are not supported by OpenTelemetry (OTel) SDKs. This article will guide you on how to use context propagation explicitly with these message queues. - Source: dev.to / 29 days ago

• NATS: First Impressions

  Https://nats.io/ (Tracker removed) > Connective Technology for Adaptive Edge & Distributed Systems > An Introduction to NATS - The first screencast I guess I don't need to know what it is. - Source: Hacker News / about 1 month ago

• Sequential and parallel execution of long-running shell commands

  Pueue dumps the state of the queue to the disk as JSON every time the state changes, so when you have a lot of queued jobs this results in considerable disk io. I actually changed it to compress the state file via zstd which helped quite a bit but then eventually just moved on to running NATS [1] locally. [1] https://nats.io/. - Source: Hacker News / about 1 month ago

• Interview with Sebastian Holstein, Founder of Qaze

  During our interview, we referred to NATS quite a few times! If you want to learn more about it, Sebastian suggests this tutorial series. - Source: dev.to / about 1 month ago

• Revolutionizing Real-Time Alerts with AI, NATs and Streamlit

  Imagine you have an AI-powered personal alerting chat assistant that interacts using up-to-date data. Whether it's a big move in the stock market that affects your investments, any significant change on your shared SharePoint documents, or discounts on Amazon you were waiting for, the application is designed to keep you informed and alert you about any significant changes based on the criteria you set in advance... - Source: dev.to / 2 months 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