Amazon Neptune 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 #8 with an average rating of 8.3, while Google is ranked #10 with an average rating of 9.0. Amazon Web Services (AWS) holds a 7.2% mindshare in MND, compared to Google’s 5.2% mindshare. Additionally, 100% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Google users who would recommend it.

Amazon Neptune

Read 4 Amazon Neptune reviews

769 Views
769 Comparison Views

100% willing to recommend

Google Cloud Bigtable

Read 9 Google Cloud Bigtable reviews

776 Views
590 Comparison Views

100% willing to recommend

Amazon Neptune

Google Cloud Bigtable

Comparison Buyer's Guide

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Executive SummaryUpdated on Jan 15, 2026

Google Cloud Bigtable and Amazon Neptune compete in the scalable, high-performance database solutions category, each with unique strengths. Google Cloud Bigtable seems to hold the upper hand in scalability and low-latency performance for massive workloads, while Amazon Neptune stands out with its graph database capabilities.

Features: Google Cloud Bigtable provides immense scalability, supports real-time analytics, and is ideal for IoT applications. It enables low-latency reads and writes suited for high-volume transactions. Amazon Neptune supports graph-based data models and is optimized for complex relationships and queries, integrating with other AWS services.

Ease of Deployment and Customer Service: Google Cloud Bigtable offers smooth deployment with clear documentation and integration with Google Cloud services. Amazon Neptune provides seamless integration with the AWS ecosystem, useful for graph database applications, although deployment and management can be complex for broader uses.

Pricing and ROI: Google Cloud Bigtable uses a pay-as-you-go model, favoring businesses needing vast data throughput, while Amazon Neptune may have higher setup costs for complex graph queries, but gives strong ROI in graph analytics. Google Cloud Bigtable tends to be more cost-effective for general use, whereas Neptune is advantageous for graph-focused projects.

To learn more, read our detailed Amazon Neptune vs. Google Cloud Bigtable Report (Updated: December 2025).

Buyer's Guide

Amazon Neptune vs. Google Cloud Bigtable

December 2025

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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 Neptune

Ranking in Managed NoSQL Databases

8th

Average Rating

8.6

Reviews Sentiment

4.5

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 (6th)

Mindshare comparison

As of January 2026, in the Managed NoSQL Databases category, the mindshare of Amazon Neptune is 7.2%, down from 15.4% compared to the previous year. The mindshare of Google Cloud Bigtable is 5.2%, down from 6.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Managed NoSQL Databases Market Share Distribution
Product	Market Share (%)
Amazon Neptune	7.2%
Google Cloud Bigtable	5.2%
Other	87.6%

Managed NoSQL Databases

Featured Reviews

Reviewer3028812

Back End Developer at Zeta

Multiple graph models and languages support lead to efficient use, yet community growth brings challenges

The onboarding part and documentation where we could ideally use Amazon Neptune is excellent. Amazon Neptune as a product by AWS is exceptional because it supports multiple graph models such as RDF and property graph. It also has support for multiple querying languages such as Gremlin, SparkQL, and OpenCypher. It is very comprehensive in supporting every requirement we had at Zetta. Amazon Neptune's best features include its multiple servers, each supporting different languages such as OpenCypher, SparkQL, and RDF. For the same RDF graph or property graph, we could use multiple languages to query on different servers. This is exceptional because we have one graph DB with two endpoints exposed where we could interact with different languages on the same graph. Additionally, Amazon has a Sagemaker Jupyter Notebook which interacts with the Amazon Neptune database itself, providing a clean UI for representing nodes since the Jupyter Notebook has predefined graph representation capabilities through queries.

Read full review

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.

Read full review

Quotes from Members

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

Pros

"Relational databases are never good at identifying patterns in graphs or other similar relationships, whereas Amazon Neptune is."

"The initial setup is actually simple."

"Amazon Neptune as a product by AWS is exceptional because it supports multiple graph models such as RDF and property graph, and it also has support for multiple querying languages such as Gremlin, SparkQL, and OpenCypher, making it very comprehensive in supporting every requirement we had at Zetta."

"I like the drive and the support of this program."

"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."

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

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

"The most valuable feature is the backup and replication service."

"The main benefit I receive from Google Cloud Bigtable is the managed service part."

"It's very user-friendly where streaming data is required."

More Google Cloud Bigtable pros

Cons

"In my scenario, the integration wasn't easy because ................in Java."

"Amazon Neptune could improve by spreading more awareness for others to have an understanding of the solution because the technology is fairly new. The developer community and larger community do not understand it yet."

"We had a strict time constraint, and it took many sleepless nights to find information in the documentation."

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

"The pricing of the solution needs to be improved."

"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."

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

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

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

"The cost of this product is too expensive."

Pricing and Cost Advice

"Microsoft Azure and Amazon AWS are on par for pricing and Google has been raising its prices."

"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

19%

Computer Software Company

12%

University

12%

Insurance Company

Computer Software Company

Financial Services Firm

University

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	6
Large Enterprise	3

Questions from the Community

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

The cost aspects were managed by our SRE team who provisioned the instances. The pricing structure is similar to how EC2 instance pricing varies. I was informed that it was somewhat expensive, thou...

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What needs improvement with Amazon Neptune?

The main issue was the limited community of Amazon Neptune users, which meant everything needed to be explored independently. Although this was adventurous, it required more time investment in the ...

See all answers

What is your primary use case for Amazon Neptune?

We managed traffic at Zetta, and traffic would be moving between multiple services in our microservice architecture. Because of this setup, we were using Amazon Neptune to understand how many reque...

See all answers

What do you like most about Google Cloud Bigtable?

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

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

Comparisons

Neo4j AuraDB vs Amazon Neptune

Compared 28% of the time

Microsoft Azure Cosmos DB vs Amazon Neptune

Compared 22% of the time

Amazon DynamoDB vs Amazon Neptune

Compared 14% of the time

MongoDB Atlas vs Amazon Neptune

Compared 12% of the time

Amazon DocumentDB vs Amazon Neptune

Compared 10% of the time

More Amazon Neptune Competitors

Microsoft Azure Cosmos DB vs Google Cloud Bigtable

Compared 25% of the time

Amazon DynamoDB vs Google Cloud Bigtable

Compared 18% of the time

MongoDB Enterprise Advanced vs Google Cloud Bigtable

Compared 16% of the time

Amazon Keyspaces vs Google Cloud Bigtable

Compared 12% of the time

Amazon Timestream vs Google Cloud Bigtable

Compared 7% of the time

More Google Cloud Bigtable Competitors

Product Reports

Buyer's Guide

Amazon Neptune

January 2026

Download Amazon Neptune product report

Buyer's Guide

Managed NoSQL Databases

January 2026

Download Google Cloud Bigtable product report

Also Known As

No data available

Google BigTable

Overview

Amazon Neptune is a fast, reliable, fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Amazon Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency. Amazon Neptune supports popular graph models Property Graph and W3C's RDF, and their respective query languages Apache TinkerPop Gremlin and SPARQL, allowing you to easily build queries that efficiently navigate highly connected datasets. Neptune powers graph use cases such as recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security.

Amazon Neptune is highly available, with read replicas, point-in-time recovery, continuous backup to Amazon S3, and replication across Availability Zones. Neptune is secure with support for HTTPS encrypted client connections and encryption at rest. Neptune is fully managed, so you no longer need to worry about database management tasks such as hardware provisioning, software patching, setup, configuration, or backups.

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

Intuit, Pearson, Samsung, Ignition One, Lifeomic, Blackfynn, Paysense

Cognite, Dow Jones, Loblaw Digital

Buyer's Guide

Amazon Neptune vs. Google Cloud Bigtable

December 2025

Free Report: Amazon Neptune vs. Google Cloud Bigtable

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