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GeoSpock VS Google Cloud Dataproc

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

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

GeoSpock logo GeoSpock

GeoSpock is the platform for data lake management, providing a unified view of the data assets within an organization and making it easily accessible.

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • GeoSpock Landing page
    Landing page //
    2022-04-24
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

GeoSpock videos

+ Add

Introducing GeoSpock DB

Google Cloud Dataproc videos

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Dataproc

Category Popularity

0-100% (relative to GeoSpock and Google Cloud Dataproc)

GeoSpock

Google Cloud Dataproc

Development
57 57%
Development
43% 43
Data Dashboard
27 27%
Data Dashboard
73% 73
Office & Productivity
100 100%
Office & Productivity
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using GeoSpock and Google Cloud Dataproc. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Google Cloud Dataproc seems to be more popular. It has been mentiond 3 times since March 2021. 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.

GeoSpock mentions (0)

We have not tracked any mentions of GeoSpock yet. Tracking of GeoSpock recommendations started around Apr 2022.

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 GeoSpock and Google Cloud Dataproc, you can also consider the following products

Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.

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

Apache Zeppelin - A web-based notebook that enables interactive data analytics.

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

Delta Lake - Application and Data, Data Stores, and Big Data Tools

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

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