Amazon DynamoDB vs Google Cloud Bigtable comparison

Amazon Web Services (AWS) and Google are both solutions in the Managed NoSQL Databases category. Amazon Web Services (AWS) is ranked #2 with an average rating of 8.1, while Google is ranked #10 with an average rating of 8.0. Amazon Web Services (AWS) holds a 10.4% mindshare in MND, compared to Google’s 5.7% mindshare. Additionally, 97% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Google users who would recommend it.

Amazon DynamoDB

Read 45 Amazon DynamoDB reviews

2,600 Views
2,600 Comparison Views

97% willing to recommend

Google Cloud Bigtable

Read 9 Google Cloud Bigtable reviews

1,518 Views
1,032 Comparison Views

100% willing to recommend

Amazon DynamoDB

Google Cloud Bigtable

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Executive SummaryUpdated on Jan 15, 2026

Google Cloud Bigtable and Amazon DynamoDB are competing cloud-based NoSQL database services, each designed to handle substantial amounts of structured data. While Google Cloud Bigtable excels in scalability and big data analytics integration within Google Cloud services, Amazon DynamoDB offers a more comprehensive feature set, appealing for its flexibility and global reach, thereby gaining an edge despite its pricing.

Features: Google Cloud Bigtable is renowned for data processing speed, scalability, and seamless integration with Google's ecosystem, enhancing analytical workloads. Amazon DynamoDB provides flexible data modeling, global distribution support, and built-in serverless operations, highly suitable for developers needing high concurrency.

Room for Improvement: Google Cloud Bigtable could enhance its user interface and data migration capabilities to further simplify usage for enterprises transitioning from on-premises systems. Amazon DynamoDB might benefit from enhanced query flexibility and reduced pricing complexity to appeal to a broader user base.

Ease of Deployment and Customer Service: Google Cloud Bigtable offers easy deployment with strong documentation and an automated setup, though initial configuration may need professional expertise. Amazon DynamoDB provides a user-friendly deployment process backed by extensive support resources, easing onboarding for new users.

Pricing and ROI: Google Cloud Bigtable's pricing structure is competitive for long-term data storage, favoring large-scale applications that result in significant ROI for big data solutions. Amazon DynamoDB, despite higher potential costs, provides notable ROI through efficient scalability and reduced operational overhead with its serverless architecture.

To learn more, read our detailed Amazon DynamoDB vs. Google Cloud Bigtable Report (Updated: June 2026).

Buyer's Guide

Amazon DynamoDB vs. Google Cloud Bigtable

June 2026

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Review summaries and opinions

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

Categories and Ranking

Amazon DynamoDB

Ranking in Managed NoSQL Databases

2nd

Average Rating

8.2

Reviews Sentiment

6.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Google Cloud Bigtable

Ranking in Managed NoSQL Databases

10th

Average Rating

8.6

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

Non-Relational Databases (4th)

Mindshare comparison

As of June 2026, in the Managed NoSQL Databases category, the mindshare of Amazon DynamoDB is 10.4%, down from 16.3% compared to the previous year. The mindshare of Google Cloud Bigtable is 5.7%, up from 5.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Managed NoSQL Databases Mindshare Distribution
Product	Mindshare (%)
Amazon DynamoDB	10.4%
Google Cloud Bigtable	5.7%
Other	83.9%

Managed NoSQL Databases

Featured Reviews

DeepakGurung

Lead SRE at JavaTech

Has improved infrastructure availability and simplified integration through reliable cloud-based data management

Amazon DynamoDB is readily available, and we do not have to worry about downtime unless there is a global outage. From a cost perspective, it presents a challenge. The primary feature is constant availability without concerns about server maintenance or ensuring database uptime, as AWS manages everything from their end. We simply set up the database and allocate it to customers according to their requirements, making it an easy and smooth transition. Regarding security, being in the cloud provides numerous security features. Amazon DynamoDB operates at the backend within our three-tier architecture. We have front hosting, business logic or application server in the middle, and databases at the backend. Additionally, we implement security layers such as SSL, creating a highly secure environment. The solution has proven to be reliable thus far.

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Akash Shanker

Team Lead at a financial services firm with 5,001-10,000 employees

Consistent performance and seamless cloud integration enhance analytics capabilities while reducing management complexity

One point for improvement in Google Cloud Bigtable is that people have confusion in mapping. There are many similar products available, and Google has managed services for similar products as well. It would be easier if the journey of knowing when to use Google Cloud Bigtable versus other Cloud SQL and alternates such as Cloud Spanner is made clearer for users. Regarding additional functionality for Google Cloud Bigtable, I am uncertain if LLMs can be integrated or if Google Cloud Bigtable can act as a vector store for LLM-specific use cases where we are interacting or using generative AI capabilities.

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Quotes from Members

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

Pros

"We directly pass the JSON value to Amazon DynamoDB, which is why Amazon DynamoDB is faster than relational databases."

"Speed is the most valuable feature. The speed to store and retrieve data from it."

"The possibility of managing documents is the most valuable aspect of the solution, and I like the fact that I don't have to define the fields."

"The fact that it is so easy to create tables and provision for known throughput saved us a lot of time, especially because we are deploying multiple environments and multiple regions."

"Stability-wise, I rate the solution a ten out of ten. I've never faced any problems."

"It offers quick performance and rapid data retrieval, often providing limited data initially but scaling up to fulfill larger demands seamlessly."

"DynamoDB is a key-value database, and it's valuable if you have simple scan queries and don't need to do point searches."

"The platform is easy to develop and configure."

More Amazon DynamoDB pros

"The solution is very stable; we've never experienced bugs or glitches, we haven't had crashes, and it works well and as expected 100% of the time."

"Stability-wise, it is a simple solution. I rate the solution's stability a ten out of ten."

"Scalability-wise, I rate the solution a ten out of ten."

"This solution is much more scalable than more traditional databases - at least the ones we are aware of."

"If you have a lot of data, it's really scalable and it's competitive."

"The solution is very convenient."

"Bigtable is very user-friendly where streaming data is required."

"Bigtable is faster than other competitors in the market. It helps us collate all the data, and the security features are great. The latency is low, and the computation speed is fantastic. Bigtable is also a managed service, so you don't have to worry about anything aside from analyzing the data ingested."

More Google Cloud Bigtable pros

Cons

"Maybe the documentation could be improved a bit. Sometimes, it's a little confusing, and people can easily be mistaken about DynamoDB."

"The design patterns and the documentation for this solution could be improved."

"The pricing for larger databases is higher."

"I would rate the stability a seven out of ten. We faced some configuration issues."

"In future releases, I would like a feature that lets us store information about public holidays or weekends. When customers call during those closed periods, we could use DynamoDB to trigger an automatic message. So this would eliminate the need for agents to manually inform customers."

"I would also like to see improvements in indexing in Amazon DynamoDB because when we change the indexing, it takes quite a bit of time, and we lack joins in the table; additionally, we have query limits concerning how much we can query at one single time, which becomes expensive when dealing with a large dataset, such as when we had around 10 million rows, and scanning that table was very costly."

"I initially faced issues with the solution's stability, performance, and security."

"Previously, only 64 KB could be used, and later, I think, it was about 400 KB. If the tool could have an additional 10 MB to offer, then the tool could be easier to use."

More Amazon DynamoDB cons

"When it comes to complex queries, a user can't get any help from a drop-down box and pick columns. It would be great if some improvements could be made in the aforementioned area concerning the solution."

"Improvement should be made as per customer recommended and requirements."

"I've used Bigtable for about three or four years."

"This product needs better security and transparency, and the price should be reduced."

"It would be nice if the pay-as-you-go license were a little cheaper."

"The program is rather expensive - it depends on the size of your data."

"The lagging problem of the product I face is an area of concern where improvements are required."

"The cost of this product is too expensive."

More Google Cloud Bigtable cons

Pricing and Cost Advice

"The pricing is based on Lambda function usage. So, if a Lambda function is invoked with every call, and we receive 5,000 calls daily, that means 5,000 Lambda invocations."

"On a scale of one to ten, where one is a high price and ten is a low price, I rate the pricing a seven. It is not the cheapest, but it is not the costliest either."

"The solution is cheaper than Cosmos DB."

"It is costly. To reduce the costs, users need to read the node in front of it. For read-heavy groups, cache optimization can help manage costs.I can't disclose specific pricing, but it's competitive compared to others in the market, and this information is easily accessible online"

"Given the services and benefits provided by AWS, the solution's pricing is average."

"I can say that it is not the cheapest one because if we had our own kind of storage solution, our own hosting, and instead of using the cloud, we opted for some other method, it would have been a tool of a lower cost."

"It is a little expensive."

"The solution's pricing is good, and it's not expensive."

More Amazon DynamoDB pricing and cost advice

"I would like to see better pricing. It is not too expensive, but it isn't cheap either."

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Construction Company

11%

Computer Software Company

10%

Manufacturing Company

Financial Services Firm

17%

Manufacturing Company

10%

Comms Service Provider

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	24
Midsize Enterprise	1
Large Enterprise	19

By reviewers
Company Size	Count
Small Business	6
Large Enterprise	4

Questions from the Community

What needs improvement with Amazon DynamoDB?

In terms of improvement for Amazon DynamoDB, I can see that it supports a very good amount of querying, but if they can enhance that part by providing aggregation functions similar to SQL and other...

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What is your primary use case for Amazon DynamoDB?

Amazon DynamoDB is primarily used for data storage since it is a non-structured database.A specific example of how I use Amazon DynamoDB for data storage in my work is that we use it in correlation...

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What advice do you have for others considering Amazon DynamoDB?

My advice for others looking into using Amazon DynamoDB would be that it depends on the architecture needs and budget; if they aim for cost-efficiency, they should use Amazon DynamoDB, but if they ...

See all answers

What needs improvement with Google Cloud Bigtable?

See all answers

What is your primary use case for Google Cloud Bigtable?

My main use case for Google Cloud Bigtable is mainly for advertisement-related analytics-related use cases.

See all answers

What advice do you have for others considering Google Cloud Bigtable?

Regarding integration with Google Cloud Bigtable and other Google Cloud services such as Dataflow, Dataproc, and BigQuery, we have not done that integration, but there are connectors available. Som...

See all answers

Comparisons

Microsoft Azure Cosmos DB vs Amazon DynamoDB

Compared 17% of the time

MongoDB Atlas vs Amazon DynamoDB

Compared 11% of the time

Google Cloud Firestore vs Amazon DynamoDB

Compared 10% of the time

Amazon Timestream vs Amazon DynamoDB

Compared 9% of the time

Amazon Keyspaces vs Amazon DynamoDB

Compared 8% of the time

More Amazon DynamoDB Competitors

Microsoft Azure Cosmos DB vs Google Cloud Bigtable

Compared 16% of the time

Amazon Keyspaces vs Google Cloud Bigtable

Compared 11% of the time

MongoDB Enterprise Advanced vs Google Cloud Bigtable

Compared 9% of the time

Timescale vs Google Cloud Bigtable

Compared 7% of the time

Oracle NoSQL Database Cloud vs Google Cloud Bigtable

Compared 6% of the time

More Google Cloud Bigtable Competitors

Product Reports

Buyer's Guide

Amazon DynamoDB

June 2026

Download Amazon DynamoDB product report

Buyer's Guide

Google Cloud Bigtable

June 2026

Download Google Cloud Bigtable product report

Also Known As

No data available

Google BigTable, BigTable

Overview

Amazon DynamoDB offers unmatched scalability, fast performance, and seamless cloud integration. It's designed to handle diverse data types with NoSQL flexibility, providing automatic scaling, low latency, and easy AWS integration.

Amazon DynamoDB stands out for its ability to efficiently manage unstructured and semi-structured data, integrating smoothly with AWS services. It features automatic scaling, global tables, and predictable latency, supporting both JSON storage and serverless operations. Users appreciate the flexibility offered by its schema design, ensuring data accessibility and security. Despite its strengths, improvements such as better documentation, enhanced querying, and expanded integration with AWS services could enhance usability. Additional features like built-in server-side encryption, cross-region replication, and data refresh scheduling would be beneficial.

What are Amazon DynamoDB's most important features?

Unmatched Scalability: Handles large data volumes effortlessly.
Automatic Scaling: Adjusts capacity based on demand.
Global Tables: Simplifies data replication across regions.
JSON Storage: Stores data in a versatile format.
Predictable Latency: Ensures consistent response times.

What benefits and ROI should be considered in reviews?

Data Flexibility: Manages both structured and unstructured data seamlessly.
Cost Efficiency: Offers competitive pricing for large data storage.
Fast Retrieval: Delivers quick data access and response.
Seamless AWS Integration: Smoothly integrates with other AWS services.

Amazon DynamoDB is utilized in industries like IoT, e-commerce, and gaming for handling sensor data, managing real-time analytics, and storing game states. Its scalability and flexibility make it ideal for companies managing extensive metadata and localization tasks. Many also utilize it for MongoDB emulation and integrating with services like AWS Lambda for streamlined automation processes.

Amazon Web Services (AWS)

Google Cloud Bigtable provides large data capacity, fast computation speed, and robust security for efficient data management. It supports seamless querying and integration, making it suitable for users transitioning to the cloud.

Google Cloud Bigtable is a managed service offering that facilitates efficient data handling through its high-performance capabilities and compatibility with other NoSQL databases. It is highly valued for its ability to manage and analyze large datasets, offering features like backup and replication, and is known for being faster than many competitors. Despite its strengths, users express concerns over its pricing, querying complexity, occasional performance lag, and difficulty in choosing between Bigtable and other services. There's also interest in its potential for integration with emerging technologies like LLMs for generative AI applications.

What are the key features of Google Cloud Bigtable?

Large Data Capacity: Supports immense volumes of data, essential for big data initiatives.
Seamless Querying: Queries large datasets with efficiency and speed.
Backup and Replication: Provides data reliability and easy recovery.
Low Latency: Ensures fast response times for queries and operations.
High Computation Speed: Offers rapid data processing capabilities.

What benefits should users look for in reviews?

Data Security: Provides robust security for sensitive data.
Ease of Analysis: Simplifies the process of collating and analyzing data.
Cloud Integration: Compatible with other NoSQL databases, aiding cloud transitions.
Fast Performance: Noted for being quicker than many alternatives.

Industries implement Google Cloud Bigtable for data management tasks such as managing large datasets, resolving production issues, and generating insights through dashboards. It is used in advertising analytics, client data evaluation in Power BI reports, and some automotive clients employ it for specialized needs, integrating business data into Google's ecosystem for efficient analysis.

Google

Sample Customers

Samsung, Snapchat, Capital One, Expedia, Tinder, Airbnb, Comcast, Lyft, Redfin, Netflix, Adobe

Cognite, Dow Jones, Loblaw Digital

Buyer's Guide

Amazon DynamoDB vs. Google Cloud Bigtable

June 2026

Free Report: Amazon DynamoDB vs. Google Cloud Bigtable

Find out what your peers are saying about Amazon DynamoDB vs. Google Cloud Bigtable and other solutions. Updated: June 2026.

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