Amazon EMR vs BigQuery comparison

Amazon Web Services (AWS) and Google are both solutions in the Cloud Data Warehouse category. Amazon Web Services (AWS) is ranked #13 with an average rating of 7.8, while Google is ranked #4 with an average rating of 8.5. Amazon Web Services (AWS) holds a 3.4% mindshare in CDW, compared to Google’s 7.7% mindshare. Additionally, 83% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Google users who would recommend it.

Amazon EMR

Read 25 Amazon EMR reviews

1,599 Views
831 Comparison Views

83% willing to recommend

BigQuery

Read 42 BigQuery reviews

2,882 Views
2,392 Comparison Views

100% willing to recommend

Amazon EMR

BigQuery

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 18, 2024

Amazon EMR and BigQuery are leading cloud-based solutions competing in the data processing and analytics market. BigQuery holds the upper hand due to its speed and flexibility, highly valued by users.

Features: Amazon EMR provides high scalability, reliability for processing large datasets, and integrates with Hadoop clusters using EC2 and S3. It requires minimal manual intervention owing to its managed nature. BigQuery is known for its fast performance, serverless platform, and built-in machine learning capabilities, allowing rapid analysis of extensive datasets.

Room for Improvement: Amazon EMR has a steep learning curve and lacks seamless web support, while customization can be challenging. It could benefit from enhanced stability and monitoring. BigQuery struggles with special character restrictions and could improve caching for external tables. There is also a need for more integrations and better machine learning features.

Ease of Deployment and Customer Service: Both platforms are primarily deployed on public clouds, with BigQuery also offering hybrid cloud options. Amazon EMR's customer support is generally knowledgeable but inconsistent. BigQuery's customer service receives mixed feedback; deploying on the public cloud is straightforward for both.

Pricing and ROI: Amazon EMR operates on a pay-as-you-go model with costs tied to infrastructure usage, requiring caution to avoid unexpected expenses. BigQuery charges based on data processed, which can be costly for small businesses but cost-effective for enterprises. Both solutions provide substantial ROI, particularly for enterprises moving from on-premise systems.

To learn more, read our detailed Amazon EMR vs. BigQuery Report (Updated: December 2025).

Buyer's Guide

Amazon EMR vs. BigQuery

December 2025

Download the complete report

Helped 881,082 peers since 2012

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

4.8

Amazon EMR offers cost savings and ROI benefits, with some users experiencing up to 20% cost reduction and high returns.

Sentiment score

5.8

BigQuery provides 27% better query performance and 17% cost reduction, offering seamless integration and efficient data management with training.

No quotes available

For more quotes and insights, download the Amazon EMR report

No quotes available

For more quotes and insights, download the BigQuery report

Customer Service

Sentiment score

7.9

Amazon EMR customer service varies, with generally responsive support despite reported delays and occasional gaps in integration assistance.

Sentiment score

7.2

Google's support is rated 8/10 for responsiveness, but challenges exist in accessibility, integration, and documentation resources.

I would rate the technical support from Amazon as ten out of ten.

reviewer2043696

Senior Technical Engineer at a transportation company with 5,001-10,000 employees

We get all call support, screen sharing support, and immediate support, so there are no problems.

reviewer1343079

Senior Chief Engineer (Enterprise System Presales/Postsales) at a tech vendor with 10,001+ employees

They help with billing, cost determination, IAM properties, security compliance, and deployment and migration activities.

Mirza Mujtaba Baig

Lead AWS Data Engineer at Fission Labs

For more quotes and insights, download the Amazon EMR report

I have been self-taught and I have been able to handle all my problems alone.

Luís Silva

Chief Technical Lead at a consultancy with 201-500 employees

rating the customer support at ten points out of ten

Jitesh Rathod

Sr. Team Lead - IT at InfoStretch

I would rate their customer service pretty good on a scale of one to 10, as they gave me access to the platform on a grant.

Mikah Sellers

Principal at Sgt Suds

For more quotes and insights, download the BigQuery report

Scalability Issues

Sentiment score

7.4

Amazon EMR efficiently scales for businesses, offering customizable cluster options to manage diverse data sizes and enterprise demands.

Sentiment score

7.8

BigQuery excels in scalability and resource management, supporting large data with seamless auto-scaling despite some processing limitations.

Scalability can be provisioned using the auto-scaling feature, EC2 instances, on-demand instances, and storage locations like block storage, S3, or file storage.

Mirza Mujtaba Baig

Lead AWS Data Engineer at Fission Labs

For more quotes and insights, download the Amazon EMR report

It is a 10 out of 10 in terms of scalability.

Luís Silva

Chief Technical Lead at a consultancy with 201-500 employees

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.

reviewer2641596

Expert Analyst at a healthcare company with 5,001-10,000 employees

For more quotes and insights, download the BigQuery report

Stability Issues

Sentiment score

7.7

Amazon EMR is praised for stability and reliability, with high ratings due to its configurability and robust features.

Sentiment score

8.3

BigQuery is a stable, efficient cloud analytics tool, with minor scalability challenges and reliable Google support for large-scale data handling.

Regular updates, patch installations, monitoring, logging, alerting, and disaster recovery activities are crucial for maintaining stability.

Mirza Mujtaba Baig

Lead AWS Data Engineer at Fission Labs

For more quotes and insights, download the Amazon EMR report

No quotes available

For more quotes and insights, download the BigQuery report

Room For Improvement

Amazon EMR users face challenges with customization, stability, onboarding, cost optimization, task speed, and demand enhanced integration and security.

BigQuery struggles with special character restrictions, high costs, complex optimization, and lacks user-friendly integration and performance flexibility.

The cost factor differs significantly. When you run Spark application on EKS, you run at the pod level, so you can control the compute cost. But in Amazon EMR, when you have to run one application, you have to launch the entire EC2.

reviewer1343079

Senior Chief Engineer (Enterprise System Presales/Postsales) at a tech vendor with 10,001+ employees

I have thoughts on what would be great to see in the product, such as AI/ML features or additional options.

reviewer2043696

Senior Technical Engineer at a transportation company with 5,001-10,000 employees

There is room for improvement with respect to retries, handling the volume of data on S3 buckets, cluster provisioning, scaling, termination, security, and integration between services like S3, Glue, Lake Formation, and DynamoDB.

Mirza Mujtaba Baig

Lead AWS Data Engineer at Fission Labs

For more quotes and insights, download the Amazon EMR report

Troubleshooting requires opening each pipeline individually, which is time-consuming.

Jitesh Rathod

Sr. Team Lead - IT at InfoStretch

BigQuery is already integrating Gemini AI into the data extraction process directly in order to reduce costs.

Luís Silva

Chief Technical Lead at a consultancy with 201-500 employees

In general, if I know SQL and start playing around, it will start making sense.

reviewer2641596

Expert Analyst at a healthcare company with 5,001-10,000 employees

For more quotes and insights, download the BigQuery report

Setup Cost

Amazon EMR pricing is variable, potentially costly, but users can manage expenses with strategic resource and instance management.

BigQuery provides flexible pricing with pay-as-you-go models, $300 credits, and competitive costs requiring mindful usage to control expenses.

Cost optimization can be achieved through instance usage, cluster sharing, and auto-scaling.

Mirza Mujtaba Baig

Lead AWS Data Engineer at Fission Labs

I would rate the price for Amazon EMR, where one is high and ten is low, as a good one.

reviewer2043696

Senior Technical Engineer at a transportation company with 5,001-10,000 employees

For more quotes and insights, download the Amazon EMR report

Being able to optimize the queries to data is critical. Otherwise, you could spend a fortune.

Luís Silva

Chief Technical Lead at a consultancy with 201-500 employees

The price is perceived as expensive, rated at eight out of ten in terms of costliness.

Jitesh Rathod

Sr. Team Lead - IT at InfoStretch

For more quotes and insights, download the BigQuery report

Valuable Features

Amazon EMR offers scalable, cost-effective big data management with integration, flexibility, security, and seamless Hadoop and Spark processing.

BigQuery excels in scalability, speed, and usability with serverless architecture, SQL support, and cost-effective data processing capabilities.

Amazon EMR helps in scalability, real-time and batch processing of data, handling efficient data sources, and managing data lakes, data stores, and data marts on file systems and in S3 buckets.

Mirza Mujtaba Baig

Lead AWS Data Engineer at Fission Labs

Amazon EMR provides out-of-the-box solutions with Spark and Hive.

reviewer1343079

Senior Chief Engineer (Enterprise System Presales/Postsales) at a tech vendor with 10,001+ employees

The features at Amazon EMR that I have found most valuable are fully customizable functions.

reviewer2043696

Senior Technical Engineer at a transportation company with 5,001-10,000 employees

For more quotes and insights, download the Amazon EMR report

It is really fast because it can process millions of rows in just a matter of one or two seconds.

reviewer2641596

Expert Analyst at a healthcare company with 5,001-10,000 employees

The features I find most valuable in this solution are the ability to run and handle large data sets in a very efficient way with multiple types of data, relational as SQL data.

Luís Silva

Chief Technical Lead at a consultancy with 201-500 employees

BigQuery processes a substantial amount of data, whether in gigabytes or terabytes, swiftly producing desired data within one or two minutes.

Jitesh Rathod

Sr. Team Lead - IT at InfoStretch

For more quotes and insights, download the BigQuery report

Categories and Ranking

Amazon EMR

Ranking in Cloud Data Warehouse

13th

Average Rating

7.8

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Hadoop (3rd)

BigQuery

Ranking in Cloud Data Warehouse

4th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of January 2026, in the Cloud Data Warehouse category, the mindshare of Amazon EMR is 3.4%, up from 3.1% compared to the previous year. The mindshare of BigQuery is 7.7%, up from 7.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Market Share Distribution
Product	Market Share (%)
BigQuery	7.7%
Amazon EMR	3.4%
Other	88.9%

Cloud Data Warehouse

Featured Reviews

reviewer1343079

Senior Chief Engineer (Enterprise System Presales/Postsales) at a tech vendor with 10,001+ employees

Has simplified ETL workflows with on-demand processing but needs improved cost efficiency and visibility

I have used AWS Glue with S3 for making tables and databases, but regarding Amazon EMR, I do not remember much as we are currently using it very minimally. This is my observation: In EKS, we have had to deploy by ourselves because EKS does not provide the Hadoop framework, Spark, Hive, and everything, but we have completed all the deployment ourselves. Whereas Amazon EMR provides all these things. The cost factor differs significantly. When you run Spark application on EKS, you run at the pod level, so you can control the compute cost. But in Amazon EMR, when you have to run one application, you have to launch the entire EC2. In Qubole, the interface was very good. I could see many details because in Amazon EMR console, very few details are available. In Qubole, at one link, you can get all the details of what is happening, how the processes are running, and the cost decreased by using Qubole. I found Qubole more user-friendly and cost-effective. From the security point of view, we had to open some access rights to Qubole, which might be a drawback in comparison to Amazon EMR which is native to AWS.

Read full review

Luís Silva

Chief Technical Lead at a consultancy with 201-500 employees

Handles large data sets efficiently and offers flexible data management capabilities

The features I find most valuable in this solution are the ability to run and handle large data sets in a very efficient way with multiple types of data, relational as SQL data. It is kind of difficult to explain, but structured data and the ability to handle large data sets are key features. The data integration capabilities in BigQuery were, in fact, an issue at the beginning. There are two types of integrations. As long as integration is within Google, it is pretty simple. When you start to try to connect external clients to that data, it becomes more complex. It is not related to BigQuery, it is related to Google security model, which is not easy to manage. I would not call it an integration issue of BigQuery, I would call it an integration issue of Google security model.

Read full review

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Top Industries

By visitors reading reviews

Financial Services Firm

22%

Educational Organization

13%

Computer Software Company

Healthcare Company

Financial Services Firm

15%

Computer Software Company

13%

Manufacturing Company

13%

Retailer

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	5
Large Enterprise	12

By reviewers
Company Size	Count
Small Business	12
Midsize Enterprise	9
Large Enterprise	20

Questions from the Community

What is your experience regarding pricing and costs for Amazon EMR?

I would rate the price for Amazon EMR, where one is high and ten is low, as a good one.

See all answers

What needs improvement with Amazon EMR?

I feel some lack of functionality in Amazon EMR. I have thoughts on what would be great to see in the product, such as AI/ML features or additional options.

See all answers

What advice do you have for others considering Amazon EMR?

I find it easy to integrate Amazon EMR with other AWS services like S3 or EC2 for data processing needs. I would rate this review as eight out of ten.

See all answers

What do you like most about BigQuery?

The initial setup process is easy.

See all answers

What is your experience regarding pricing and costs for BigQuery?

I believe the cost of BigQuery is competitive versus the alternatives in the market, but it can become expensive if the tool is not used properly. It is on a per-consumption basis, the billing, so ...

See all answers

What needs improvement with BigQuery?

There are areas that could be improved with BigQuery, such as more bolt-on capabilities and the ability to use more bolt-ons for APIs. Having more of a library of connectors would be really benefic...

See all answers

Comparisons

Snowflake vs Amazon EMR

Compared 23% of the time

Cloudera Distribution for Hadoop vs Amazon EMR

Compared 12% of the time

Apache Spark vs Amazon EMR

Compared 8% of the time

Amazon Redshift vs Amazon EMR

Compared 8% of the time

Cloudera Data Platform vs Amazon EMR

Compared 6% of the time

More Amazon EMR Competitors

Oracle Autonomous Data Warehouse vs BigQuery

Compared 20% of the time

Teradata vs BigQuery

Compared 11% of the time

Snowflake vs BigQuery

Compared 11% of the time

OpenText Analytics Database (Vertica) vs BigQuery

Compared 8% of the time

IBM Db2 Warehouse vs BigQuery

Compared 6% of the time

More BigQuery Competitors

Product Reports

Buyer's Guide

Amazon EMR

January 2026

Download Amazon EMR product report

Buyer's Guide

BigQuery

January 2026

Download BigQuery product report

Also Known As

Amazon Elastic MapReduce

No data available

Overview

Amazon Elastic MapReduce (Amazon EMR) is a web service that makes it easy to quickly and cost-effectively process vast amounts of data. Amazon EMR simplifies big data processing, providing a managed Hadoop framework that makes it easy, fast, and cost-effective for you to distribute and process vast amounts of your data across dynamically scalable Amazon EC2 instances.

Amazon Web Services (AWS)

BigQuery is an enterprise data warehouse that solves this problem by enabling super-fast SQL queries using the processing power of Google's infrastructure. ... You can control access to both the project and your data based on your business needs, such as giving others the ability to view or query your data.

Google

Sample Customers

Yelp

Information Not Available

Buyer's Guide

Amazon EMR vs. BigQuery

December 2025

Free Report: Amazon EMR vs. BigQuery

Find out what your peers are saying about Amazon EMR vs. BigQuery and other solutions. Updated: December 2025.

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