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Apache Hadoop vs Snowflake Analytics comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

ROI

Sentiment score
6.5
Apache Hadoop provides cost-effective data storage and processing, though ROI varies based on analytics use and sophistication.
Sentiment score
6.4
Snowflake Analytics boosts ROI up to 50% by optimizing costs, improving performance, and enabling simultaneous team collaboration.
 

Customer Service

Sentiment score
6.4
Customer service varies by Hadoop distributor, with Hortonworks rated highly; support depends on vendor, community resources, or external vendors.
Sentiment score
6.9
Snowflake Analytics' support receives mixed reviews; many praise responsiveness, while others face delays and struggle accessing direct help.
It's not structured support, which is why we don't use purely open-source projects without additional structured support.
 

Scalability Issues

Sentiment score
7.6
Apache Hadoop excels in scalability, allowing easy cluster expansion and efficient data handling, ideal for varied organizational needs.
Sentiment score
8.0
Snowflake Analytics excels in scalability, auto-scaling CPU/GPU resources efficiently, benefiting businesses with its adaptive cloud-based architecture.
It is a distributed file system and scales reasonably well as long as it is given sufficient resources.
Storage is unlimited because they use S3 if it is AWS, so storage has no limit.
 

Stability Issues

Sentiment score
7.3
Apache Hadoop's stability, rated 8/10, improves with newer versions, though minor issues exist with memory and data processing.
Sentiment score
8.5
Snowflake Analytics is highly rated for stability, offering reliable performance and minimal outages thanks to cloud-backed robustness.
Continuous management in the way of upgrades and technical management is necessary to ensure that it remains effective.
 

Room For Improvement

Apache Hadoop needs improved usability, integration, security, support, and performance for efficient high-volume data processing and better community resources.
Snowflake Analytics requires better orchestration, integration, performance, machine learning support, user interface, cost transparency, and AI-driven analytics capabilities.
The problem with Apache Hadoop arose when the guys that originally set it up left the firm, and the group that later owned it didn't have enough technical resources to properly maintain it.
AIML-based SQL prompt and query generation could be an area for enhancement.
Navigating the user console can be challenging, particularly when looking for details like the account ID.
 

Setup Cost

Enterprise Hadoop offers cost benefits but varies with deployment type and distribution, impacting smaller organizations more heavily.
Snowflake Analytics uses a flexible, consumption-based pricing model, balancing costs with usability for business analytics and streaming workloads.
Snowflake charges per query, which amounts to a very minor cost, such as $0.015 per query.
Snowflake is better and cheaper than Redshift and other cloud warehousing systems.
 

Valuable Features

Apache Hadoop excels with a scalable, cost-effective system handling diverse data types, integrating with tools, and supporting big data analytics.
Snowflake Analytics offers scalable, flexible, and secure data integration with standout features for large datasets and AI capabilities across major cloud platforms.
If you don't do the upgrades, the platform ages out, and that's what happened to the Hadoop content.
Running a considerable query on Microsoft SQL Server may take up to thirty minutes or an hour, while Snowflake executes the same query in less than three minutes.
It is a data offering where I can see data lineage, data governance, and data security.
 

Categories and Ranking

Apache Hadoop
Average Rating
7.8
Reviews Sentiment
6.7
Number of Reviews
40
Ranking in other categories
Data Warehouse (7th)
Snowflake Analytics
Average Rating
8.4
Reviews Sentiment
7.2
Number of Reviews
39
Ranking in other categories
Web Analytics (1st), Cloud Data Warehouse (8th)
 

Featured Reviews

Sushil Arya - PeerSpot reviewer
Provides ease of integration with the IT workflow of a business
When working with Kafka, I saw that the data came in an incremental order. The incremental data processing part is still not very effective in Apache Hadoop. If the data is already there, it can be processed very effectively, especially if the data is coming in every second. If you want to know the location of some data every second, then such data is not processed effectively in Apache Hadoop. I can say that one of the features where improvements are required revolves around the licensing cost of the tool. If the tool can build some licensing structures in a pay-per-use manner, organizations can get the look and feel of Apache Hadoop. Apache Hadoop can offer a licensing structure of the product that can be seen as similar to how AWS operates. Apache Hadoop can look into the capability of processing incremental data. The tool's setup process can be a scope of improvement. Also, it is not very simple because while doing the setup, we need to do all the server settings, including port listing and firewall configurations. If we look at other products on the market, then they can be made simpler. There are certain shortcomings when it comes to the product's technical support part, making it an area where improvements are required. The time frame for the resolution is an area that needs to be improved. The overall communication part of the technical support team also needs improvement.
KamleshPant - PeerSpot reviewer
Data ecosystem thrives with advanced governance and streaming capabilities
It is a data offering where I can see data lineage, data governance, and data security. Snowflake has a streaming capability to work with real-time streaming data and delta tables. Additionally, task management, job scheduling, and connecting multiple data sources unify my data across internal and external sources. The system ecosystem for analytics is enhanced, and AI capabilities are incorporated.
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Top Industries

By visitors reading reviews
Financial Services Firm
33%
Computer Software Company
11%
University
7%
Energy/Utilities Company
6%
Computer Software Company
19%
Retailer
13%
Financial Services Firm
9%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Apache Hadoop?
It's primarily open source. You can handle huge data volumes and create your own views, workflows, and tables. I can also use it for real-time data streaming.
What is your experience regarding pricing and costs for Apache Hadoop?
The product is open-source, but some associated licensing fees depend on the subscription level. While it might be free for students, organizations typically need to pay for their subscriptions. Th...
What needs improvement with Apache Hadoop?
The problem with Apache Hadoop arose when the guys that originally set it up left the firm, and the group that later owned it didn't have enough technical resources to properly maintain it. This wa...
What is your experience regarding pricing and costs for Snowflake Analytics?
Snowflake is better and cheaper than Redshift and other cloud warehousing systems. It's economical.
What needs improvement with Snowflake Analytics?
Most features are already available. Perhaps AIML integration might be further needed, or Snowflake is already implementing it. AIML-based SQL prompt and query generation could be an area for enhan...
 

Overview

 

Sample Customers

Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web Lab
Lionsgate, Adobe, Sony, Capital One, Akamai, Deliveroo, Snagajob, Logitech, University of Notre Dame, Runkeeper
Find out what your peers are saying about Apache Hadoop vs. Snowflake Analytics and other solutions. Updated: March 2025.
848,207 professionals have used our research since 2012.