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Impala VS Google Cloud Dataproc

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

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Contents:
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  2. » Videos
  3. » Reviews
  4. » Alternatives

Impala logo Impala

Impala is a modern, open source, distributed SQL query engine for Apache Hadoop.

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • Impala Landing page
    Landing page //
    2023-04-02
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

Impala videos

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2016 Chevrolet Impala - Review and Road Test

More videos:

  • Review - 2020 Chevrolet Impala Review | The Final Year
  • Review - Is it the END of the road for the 2019 Chevy Impala?

Google Cloud Dataproc videos

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Dataproc

Category Popularity

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

Impala

Google Cloud Dataproc

Big Data
23 23%
Big Data
77% 77
Data Dashboard
15 15%
Data Dashboard
85% 85
Databases
100 100%
Databases
0% 0
Development
0 0%
Development
100% 100

User comments

Share your experience with using Impala 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.

Impala mentions (0)

We have not tracked any mentions of Impala yet. Tracking of Impala recommendations started around Mar 2021.

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 / almost 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 Impala and Google Cloud Dataproc, you can also consider the following products

Apache Kudu - Apache Kudu is Hadoop's storage layer to enable fast analytics on fast data.

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

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

BlueData - BlueData's software platform makes it easier, faster and more cost-effective for organizations to deploy Big Data infrastructure on-premises.

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

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

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