Observable VS Google Cloud Dataflow

Observable Reviews

Google Cloud Dataflow Reviews

Observable mentions (286)

• I'm writing a new vector search SQLite Extension

  Could this be implemented in Rust? Does that project (sqlite-loadable-rs) support WASM? https://observablehq.com/@asg017/introducing-sqlite-loadable-rs. - Source: Hacker News / 11 days ago

• Show HN: An extension to track your Wikipedia adventures

  Have you tried out a tangled-tree visualization? [1] I've found it to be super useful when visualizing these sorts of relationships in a compact way. [1] https://observablehq.com/@nitaku/tangled-tree-visualization-ii. - Source: Hacker News / 11 days ago

• A feature-rich front-end drag-and-drop component library

  Maybe I'm easy to impress, but I always stop and play around with the nested tree example when I come across Sortable. It works so flawlessly, and feels very tuned to mobile dnd. It even works to arrange (and reflow) inline spans in a paragraph! I have yet to come across this functionality in a text editor.. [0]: https://observablehq.com/@dleeftink/sortable-playground. - Source: Hacker News / 19 days ago

• Parquet-WASM: Rust-based WebAssembly bindings to read and write Parquet data

  Arrow JS is just ArrayBuffers underneath. You do want to amortize some operations to avoid unnecessary conversions. I.e. Arrow JS stores strings as UTF-8, but native JS strings are UTF-16 I believe. Arrow is especially powerful across the WASM <--> JS boundary! In fact, I wrote a library to interpret Arrow from Wasm memory into JS without any copies [0]. (Motivating blog post [1]) [0]:... - Source: Hacker News / 21 days ago

• A flat map with the least error possible: The Gott-Goldberg-Vanderbei projection

  Here’s the D3 implementation (which is just an interrupted azimuthal equidistant projection): https://observablehq.com/@d3/azimuthal-equidistant-hemispheres. - Source: Hacker News / 22 days 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