Google Cloud Dataflow Reviews

Microsoft Teams Reviews

1. Boyd Richardson

   | Writer at SE | about 1 year ago
   The Ultimate Collaboration App

   s someone who works remotely, I've tried my fair share of collaboration apps. However, I have to say that Microsoft Teams has impressed me the most. It's a comprehensive app that brings together all the tools I need to communicate and collaborate with my colleagues seamlessly.

   The interface of Microsoft Teams is user-friendly and easy to navigate. I particularly love the left-hand navigation bar that provides quick access to all the features, including chats, meetings, files, and activity. The app integrates with other Microsoft apps, such as Outlook and OneDrive, making it easier to schedule meetings and access files. The chat feature is simple, yet effective, with options to create groups, share files, and use emojis and GIFs.

   🏁 Competitors: Discord, Slack

   👍 Pros:    Well-integrated|Collaboration|Feature rich

   👎 Cons:    Overwhelming for first time user|Mobile app lacks features|Can be slow

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

Microsoft Teams mentions (0)