Software Alternatives, Accelerators & Startups

MonetDB VS Amazon EMR

Compare MonetDB VS Amazon EMR and see what are their differences

MonetDB logo MonetDB

Column-store database

Amazon EMR logo Amazon EMR

Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
  • MonetDB Landing page
    Landing page //
    2023-09-23
  • Amazon EMR Landing page
    Landing page //
    2023-04-02

MonetDB videos

MonetDB on Azure - Deployment and First Query

More videos:

  • Review - My uninformed attempt at running open source high speed monetDB
  • Review - DB2 — Chapter 03 — Video #10 — Column storage in MonetDB, NSM vs. DSM, positional BAT "joins"

Amazon EMR videos

Amazon EMR Masterclass

More videos:

  • Review - Deep Dive into What’s New in Amazon EMR - AWS Online Tech Talks
  • Tutorial - How to use Apache Hive and DynamoDB using Amazon EMR

Category Popularity

0-100% (relative to MonetDB and Amazon EMR)
Relational Databases
100 100%
0% 0
Data Dashboard
0 0%
100% 100
Databases
100 100%
0% 0
Big Data
5 5%
95% 95

User comments

Share your experience with using MonetDB and Amazon EMR. For example, how are they different and which one is better?
Log in or Post with

Social recommendations and mentions

Based on our record, Amazon EMR seems to be more popular. It has been mentiond 10 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.

MonetDB mentions (0)

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

Amazon EMR mentions (10)

  • 5 Best Practices For Data Integration To Boost ROI And Efficiency
    There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: about 1 year ago
  • What compute service i should use? Advice for a duck-tape kind of guy
    I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 2 years ago
  • Processing a large text file containing millions of records.
    This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: about 2 years ago
  • How to use Spark and Pandas to prepare big data
    Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago
  • Beginner building a Hadoop cluster
    Check out https://aws.amazon.com/emr/. Source: about 2 years ago
View more

What are some alternatives?

When comparing MonetDB and Amazon EMR, you can also consider the following products

DuckDB - DuckDB is an in-process SQL OLAP database management system

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

ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

DataGrip - Tool for SQL and databases

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