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Apache Hadoop vs BigQuery 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 offers cost-effective storage and processing, with varying returns based on analytics sophistication and workload optimization.
Sentiment score
8.6
BigQuery users report up to 75% cost savings and improved performance, with training yielding full benefits in one year.
 

Customer Service

Sentiment score
6.5
Apache Hadoop's support varies, with high satisfaction from vendor packages, responsive teams, and helpful documentation and community.
Sentiment score
7.1
BigQuery's customer service is efficient for premium users, but others face challenges and rely on documentation and partners.
rating the customer support at ten points out of ten
 

Scalability Issues

Sentiment score
7.6
Apache Hadoop offers scalable data management for large-scale deployments, efficiently supports diverse users and adapts across industries.
Sentiment score
7.9
BigQuery is highly scalable and efficient, ideal for large operations, but may have limitations with extremely large datasets.
The scalability is definitely good because we are migrating to the cloud since the computers on the premises or the big database we need are no longer enough.
 

Stability Issues

Sentiment score
7.4
Apache Hadoop is stable, especially newer versions, with occasional issues in setup, memory, and online data ingestion.
Sentiment score
8.5
BigQuery is highly stable and reliable, with efficient data processing despite some regional scalability challenges.
 

Room For Improvement

Apache Hadoop requires enhanced compatibility, improved usability, real-time processing, better security, modern interfaces, and cost-effective solutions to boost adoption.
BigQuery faces challenges in user-friendliness, performance, cost, regional access, and integration, affecting its appeal to SMBs.
Troubleshooting requires opening each pipeline individually, which is time-consuming.
In general, if I know SQL and start playing around, it will start making sense.
 

Setup Cost

Apache Hadoop is cost-effective for large-scale deployments, but smaller enterprises face higher expenses despite potential cloud cost savings.
BigQuery offers affordable, competitive pricing with flexible options; careful data management is vital to optimize costs and avoid unexpected charges.
The price is perceived as expensive, rated at eight out of ten in terms of costliness.
 

Valuable Features

Apache Hadoop offers cost-efficient, scalable data processing with HDFS, supporting large datasets and seamless integration with tools like Spark.
BigQuery offers scalable, fast data handling and analysis with machine learning integration, supporting diverse needs and seamless SQL compatibility.
It is really fast because it can process millions of rows in just a matter of one or two seconds.
BigQuery processes a substantial amount of data, whether in gigabytes or terabytes, swiftly producing desired data within one or two minutes.
 

Categories and Ranking

Apache Hadoop
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
39
Ranking in other categories
Data Warehouse (7th)
BigQuery
Average Rating
8.2
Reviews Sentiment
7.3
Number of Reviews
40
Ranking in other categories
Cloud Data Warehouse (4th)
 

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.
Sathishkumar Jayaprakash - PeerSpot reviewer
Efficient large dataset handling with seamless service integration
BigQuery allows for very fast access, and it is efficient in handling large datasets compared to other SQL databases. It integrates well with other GCP products, and creating subscriptions in the UI is straightforward. The whole ecosystem of GCP products makes BigQuery beneficial for our data-handling tasks. Additionally, it is more cost-effective compared to alternatives like AWS.
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Top Industries

By visitors reading reviews
Financial Services Firm
34%
Computer Software Company
11%
University
7%
Energy/Utilities Company
5%
Computer Software Company
16%
Financial Services Firm
14%
Manufacturing Company
12%
Retailer
7%
 

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?
Hadoop lacks OLAP capabilities. I recommend adding a Delta Lake feature to make the data compatible with ACID properties. Also, video and audio streaming import issues could be improved to ensure p...
What do you like most about BigQuery?
The initial setup process is easy.
What is your experience regarding pricing and costs for BigQuery?
The price is perceived as expensive, rated at eight out of ten in terms of costliness. Still, it offers significant cost savings.
What needs improvement with BigQuery?
When I execute a query, the dashboard doesn't always present the output seamlessly. Troubleshooting requires opening each pipeline individually, which is time-consuming. Moreover, pricing, the abse...
 

Comparisons

 

Overview

 

Sample Customers

Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web Lab
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Find out what your peers are saying about Apache Hadoop vs. BigQuery and other solutions. Updated: January 2025.
831,881 professionals have used our research since 2012.