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VoltDB VS Google Cloud Dataproc

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

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

VoltDB logo VoltDB

In-memory relational DBMS capable of supporting millions of database operations per second

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • VoltDB Landing page
    Landing page //
    2023-09-17
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

VoltDB videos

+ Add

VoltDB Explained in 2 Minutes

More videos:

  • Review - CMU Database Systems - 25 Ethan Zhang [VoltDB] (Fall 2018)
  • Review - VoltDB Founder/Engineer: Transactional Streaming - If You Can Compute It, You Can Probably Stream It

Google Cloud Dataproc videos

+ Add

Dataproc

Category Popularity

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

VoltDB

Google Cloud Dataproc

Databases
100 100%
Databases
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
NoSQL Databases
100 100%
NoSQL Databases
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using VoltDB 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.

VoltDB mentions (0)

We have not tracked any mentions of VoltDB yet. Tracking of VoltDB 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 / 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 VoltDB and Google Cloud Dataproc, you can also consider the following products

Microsoft SQL Server Compact - Bring Microsoft SQL Server 2017 to the platform of your choice. Use SQL Server 2017 on Windows, Linux, and Docker containers.

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

UnQLite - UnQLite is a in-process software library which implements a self-contained, serverless...

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

CompactView - Viewer for Microsoft® SQL Server® CE database files (sdf)

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

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