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SQream VS Google Cloud Dataproc

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

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SQream logo SQream

SQream empowers organizations to analyze the full scope of their Massive Data, from terabytes to petabytes, to achieve critical insights which were previously unattainable.

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • SQream Landing page
    Landing page //
    2023-09-17

SQream is a data analytics acceleration platform built especially for massive data - from terabytes to petabytes. SQream takes queries down from days to hours and hours to minutes. The SQream platform provides the ability to analyze more data, faster, with multiple dimensions and cuts data preparation significantly by enabling ad-hoc querying on raw data. Leading global organizations in telecommunications, healthcare, ad-tech, retail and more rely on SQream to achieve critical business insights and potentially valuable BI across their massive data stores.

  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

SQream videos

+ Add

SQream DB v2020.1 - Product review and demo

More videos:

  • Review - Introducing SQream DB - The GPU-accelerated data warehouse for massive data
  • Review - SQream DB, GPU-accelerated data warehouse

Google Cloud Dataproc videos

+ Add

Dataproc

Category Popularity

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

SQream

Google Cloud Dataproc

Data Dashboard
12 12%
Data Dashboard
88% 88
Big Data
15 15%
Big Data
85% 85
Big Data Infrastructure
100 100%
Big Data Infrastructure
0% 0
Development
0 0%
Development
100% 100

User comments

Share your experience with using SQream 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 should be more popular than SQream. 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.

SQream mentions (1)

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: about 2 years ago

What are some alternatives?

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

GridGain In-Memory Data Fabric - TheGridGain In-Memory Computing Platform is a comprehensive solution provides speed and scale for data intensive applications across any data store

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

Panoply - Panoply is a smart cloud data warehouse

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

Apache ORC - Apache ORC is a columnar storage for Hadoop workloads.

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

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