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Observable VS Google Cloud Dataproc

Compare Observable VS Google Cloud Dataproc and see what are their differences

Observable logo Observable

Interactive code examples/posts

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • Observable Landing page
    Landing page //
    2023-10-09
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

Observable videos

Observable Overview

More videos:

  • Review - observablehq.com review observable hq data analysis
  • Review - Hands-on Data Visualization with Observable Plot

Google Cloud Dataproc videos

Dataproc

Category Popularity

0-100% (relative to Observable and Google Cloud Dataproc)
Data Visualization
100 100%
0% 0
Data Dashboard
60 60%
40% 40
Big Data
0 0%
100% 100
Data Science And Machine Learning

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Observable and Google Cloud Dataproc

Observable Reviews

Top 10 Grafana Alternatives in 2024
Observable is a Grafana alternative that enables users to visualize data via charts and dashboards using code.
Source: middleware.io
Embedded analytics in B2B SaaS: A comparison
A few options were disregarded from the start due to a hefty price tag, these were Looker, Tableau, Power BI, GoodData. A few options like Trevor.io, Preset, Observable were disregarded as they did not seem to fit our criteria (based on the evaluation matrix).
Source: medium.com

Google Cloud Dataproc Reviews

We have no reviews of Google Cloud Dataproc yet.
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Social recommendations and mentions

Based on our record, Observable seems to be a lot more popular than Google Cloud Dataproc. While we know about 287 links to Observable, we've tracked only 3 mentions of Google Cloud Dataproc. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Observable mentions (287)

  • Modos Paper Monitor Pre-Launch on Crowd Supply
    Curious to see whether more recent dithering approaches would produce better results. They don't even have to be more resource hungry than the classic Bayer or Floyd-Steinberg dithers! Interleaved Gradient Noise[0][1][2] comes to mind as an alternative to Bayer, and it can even be approximated quite well with just 8-bit operations! Basically, use the following function to determine your threshold based on pixel... - Source: Hacker News / 6 days ago
  • 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 / 24 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 / 24 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 / about 1 month 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 / about 1 month ago
View more

Google Cloud Dataproc mentions (3)

  • Connecting IPython notebook to spark master running in different machines
    I have also a spark cluster created with google cloud dataproc. Source: about 1 year ago
  • Why we don’t use Spark
    Specifically, we heavily rely on managed services from our cloud provider, Google Cloud Platform (GCP), for hosting our data in managed databases like BigTable and Spanner. For data transformations, we initially heavily relied on DataProc - a managed service from Google to manage a Spark cluster. - Source: dev.to / about 2 years ago
  • Data processing issue
    With that, the best way to maximize processing and minimize time is to use Dataflow or Dataproc depending on your needs. These systems are highly parallel and clustered, which allows for much larger processing pipelines that execute quickly. Source: over 2 years ago

What are some alternatives?

When comparing Observable and Google Cloud Dataproc, you can also consider the following products

RunKit - RunKit notebooks are interactive javascript playgrounds connected to a complete node environment right in your browser. Every npm module pre-installed.

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

HortonWorks Data Platform - The Hortonworks Data Platform is a 100% open source distribution of Apache Hadoop that is truly...