Amazon Neptune vs Neo4j AuraDB comparison

Amazon Web Services (AWS) and Neo4j are both solutions in the Managed NoSQL Databases category. Amazon Web Services (AWS) is ranked #7 with an average rating of 8.3, while Neo4j is ranked #8 with an average rating of 8.9. Amazon Web Services (AWS) holds a 7.7% mindshare in MND, compared to Neo4j’s 5.2% mindshare. Additionally, 100% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Neo4j users who would recommend it.

Amazon Neptune

Read 4 Amazon Neptune reviews

794 Views
794 Comparison Views

100% willing to recommend

Neo4j AuraDB

Read 7 Neo4j AuraDB reviews

539 Views
539 Comparison Views

100% willing to recommend

Amazon Neptune

Neo4j AuraDB

Comparison Buyer's Guide

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Executive SummaryUpdated on Mar 3, 2025

Amazon Neptune and Neo4j AuraDB are competing in the graph database services category. Neo4j AuraDB has an advantage for intricate data models due to its advanced graph data processing capabilities.

Features: Amazon Neptune offers high scalability, seamless AWS system integration, and support for popular graph models. Neo4j AuraDB provides sophisticated graph analytics, deeper insights into complex relationships, and advanced graph-specific functionalities.

Ease of Deployment and Customer Service: Amazon Neptune simplifies deployment within AWS and offers extensive support options. Neo4j AuraDB has an easy cloud-based deployment process with dedicated support channels, suitable for graph-centric projects.

Pricing and ROI: Amazon Neptune aligns with AWS service models, offering potential cost savings through integration and usage-based scaling. Neo4j AuraDB, though premium, delivers significant ROI through advanced capabilities, often justifying its higher setup cost for data-intensive operations.

To learn more, read our detailed Amazon Neptune vs. Neo4j AuraDB Report (Updated: September 2025).

Buyer's Guide

Amazon Neptune vs. Neo4j AuraDB

September 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

7th

Average Rating

8.6

Reviews Sentiment

4.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Neo4j AuraDB

Ranking in Managed NoSQL Databases

8th

Average Rating

8.8

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of October 2025, in the Managed NoSQL Databases category, the mindshare of Amazon Neptune is 7.7%, down from 14.9% compared to the previous year. The mindshare of Neo4j AuraDB is 5.2%, down from 5.4% 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	7.7%
Neo4j AuraDB	5.2%
Other	87.1%

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.

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Jeff Dalgliesh

Founder at data2

Room for improvement in interface capabilities while rapidly solving domain-specific problems

Neo4j AuraDB is a great tool for understanding connections between things. The best features Neo4j AuraDB offers are that it is easy to quickly build a solution with their tooling. Regarding the tooling, I love how fast it is that you can use NeoDash to quickly mock up a UI, and it is really nice that you can build a GraphQL endpoint to connect it to third-party applications, such as Retool or custom applications that we build for clients. Neo4j AuraDB has impacted my organization positively as it has helped me solve problems much more quickly. A specific example of a problem I solved more quickly with Neo4j AuraDB is that I was able to work with an LLM to build graph data models for domain-specific problems. The collaboration with the LLM and Neo4j AuraDB sped up my process as I'm building a tool on top of Neo4j that allows me to control how I can access data in the graph, and Neo4j had a nice interface that allowed us to work with their underlying data model.

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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

"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."

"The tool is easy to use."

"Integrating the front-end language with Neo4j AuraDB is a very easy process."

"I like the idea of graphs and nodes and the possibilities Neo4j AuraDB offers."

"The most beneficial things in terms of AuraDB are its speed, its good pricing, the multi-cloud availability."

"The best features Neo4j AuraDB offers are that it is easy to quickly build a solution with their tooling."

"From my experience, I particularly like the professional version. Initially, developers often start with the free variant. Once the project grows, we switch to the professional version, which offers multiple databases, expanded memory, and better scalability. This allows us to handle more data and use cloud scaling features."

"The most valuable features of Neo4j AuraDB include its flexible data model and broad language support."

Cons

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

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

"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."

"Some features can help if they can visualize graphs better."

"In terms of AuraDB, the conversations have always been around scalability."

"I would love to see a Retool type of interface builder with Neo4j AuraDB."

"There’s room for improvement in Neo4j AuraDB, especially on the developer side. The learning curve can be steep, and the interface for developing and pushing code can be unnecessarily complex. It might be beneficial to simplify this process to help developers ramp up more quickly. Working with graph databases like Neo4j can be more challenging than standard databases, particularly for juniors and those new to graph technology. Streamlining the development process could make it easier for new users to get up to speed. This would be particularly useful for teams with less experience in graph databases. If I could add a feature to Neo4j AuraDB, I’d focus on improving the Bloom interface. It’s excellent for visualizing smaller datasets, but navigating through it becomes challenging as the data grows—say, past 100,000nodes. The interface works well for beginners but doesn’t scale effectively for more advanced users of large datasets. I want a UI that bridges the gap between the easy-to-use Bloom interface and more complex, text-based tools. This would help manage larger datasets more efficiently and improve performance."

"I've experienced it crashing a few times, so stability could be better."

"During the product's initial setup phase, there were some issues due to disconnections in the tool's network."

Pricing and Cost Advice

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

"I am using an open-source version of Neo4j AuraDB."

"Neo4j AuraDB is reasonably priced, especially considering it removes the need for cloud administration and associated costs. It's a good deal for the professional version, as it includes managed services, which reduces the overhead compared to setting up your own infrastructure. The cost can be higher for enterprise-scale projects, but that's often due to the scale and complexity of the project rather than the product itself. Startups sometimes overestimate their needs and jump to enterprise pricing too quickly, leading to higher costs than necessary."

"The tool's enterprise edition is very expensive."

"I used the free tier."

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Top Industries

By visitors reading reviews

Financial Services Firm

20%

Computer Software Company

17%

Construction Company

University

Computer Software Company

32%

Educational Organization

11%

Financial Services Firm

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	2
Large Enterprise	1

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 ...

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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...

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What is your experience regarding pricing and costs for Neo4j AuraDB?

It has fair pricing.

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What is your primary use case for Neo4j AuraDB?

My main use case for Neo4j AuraDB is solving water optimization problems for oil and gas operations. Neo4j AuraDB helps us resolve those water optimization problems by allowing us to store knowledg...

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What advice do you have for others considering Neo4j AuraDB?

My advice to others looking into using Neo4j AuraDB is to consider how many graphs you can create as quickly as needed. I think Neo4j AuraDB is doing some amazing things. On a scale of 1-5, I rate ...

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Product Reports

Buyer's Guide

Amazon Neptune

September 2025

Download Amazon Neptune product report

Buyer's Guide

Neo4j AuraDB

September 2025

Download Neo4j AuraDB product report

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)

Neo4j AuraDB offers seamless integration with Python, Java, and Go, efficiently handles real-time data, and is hosted on AWS Cloud for reliable, scalable, and multi-cloud support across GCP, Azure, and Amazon.

Neo4j AuraDB is appreciated for its flexible data models and dedicated query language, ideal for network correlation and graph analysis. It provides scalability with expanded memory and supports multiple databases. While users enjoy its speed and AI data handling capabilities, challenges include stability, with occasional crashes and a need for a more intuitive cloud interface. Enhancements in simplifying the development process and improving the Bloom interface for large datasets are desired. Although documentation is positive, it could be streamlined. Scalability in large projects is a recurring concern alongside a more user-friendly setup for less experienced teams.

What are Neo4j AuraDB's standout features?

Seamless language integration: Works well with Python, Java, and Go.
Cloud hosting: Reliable hosting on AWS with GCP and Azure compatibility.
Scalability: Offers expanded memory and support for multiple databases.
Real-time data handling: Efficient for AI and analytics projects.
Flexible data model: Supports network correlation and relationship-centric modeling.

What benefits should users expect?

Cost-effective pricing: Multi-cloud availability ensures competitive rates.
Rapid analysis: Swiftly handles data point relationships.
Graph visualization: Enables effective illustration of graph schemas.
Project scalability: Supports resource aggregation and AI applications.

Research teams use Neo4j AuraDB to learn cipher language and gather data from platforms like Hacker News. It is vital for graph data access, participant engagement, and projects like connecting food data or investment insights. Companies needing scalable cloud interfaces and swift data analysis in generative AI contexts benefit significantly, achieving effective data point connection with robust documentation.

Neo4j

Sample Customers

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

Information Not Available

Buyer's Guide

Amazon Neptune vs. Neo4j AuraDB

September 2025

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