Amazon Neptune vs Microsoft Azure Cosmos DB comparison

Amazon Web Services (AWS) and Microsoft are both solutions in the Managed NoSQL Databases category. Amazon Web Services (AWS) is ranked #9 with an average rating of 8.3, while Microsoft is ranked #1 with an average rating of 8.3. Amazon Web Services (AWS) holds a 6.9% mindshare in MND, compared to Microsoft’s 16.0% mindshare. Additionally, 100% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 95% of Microsoft users who would recommend it.

Amazon Neptune

Read 4 Amazon Neptune reviews

855 Views
855 Comparison Views

100% willing to recommend

Microsoft Azure Cosmos DB

Read 109 Microsoft Azure Cosmos DB reviews

10,961 Views
3,946 Comparison Views

95% willing to recommend

Amazon Neptune

Microsoft Azure Cosmos DB

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Executive SummaryUpdated on Jan 25, 2026

Microsoft Azure Cosmos DB and Amazon Neptune compete in the database services category, each offering unique strengths. Azure Cosmos DB holds an edge with its extensive flexibility and robust global distribution capabilities, excelling in various data architectures, whereas Amazon Neptune's strong suit is in specialized graph database management, making it appealing for specific applications like knowledge graphs and social networks.

Features: Azure Cosmos DB offers multi-model data support, accommodating multiple APIs for a versatile approach to data architectures. It provides exceptional global distribution capabilities, enabling seamless cross-region solutions. Its comprehensive indexing strategies ensure fast and consistent data retrieval. Amazon Neptune supports complex graph data models, including Property Graphs and RDF. It delivers specialized functionalities for graph applications, allowing for efficient handling of graph workloads. Its integration with AWS services enhances its offerings for graph-specific use cases.

Ease of Deployment and Customer Service: Azure Cosmos DB is noted for straightforward deployments across multiple regions, providing a seamless experience for scaling. It is backed by consistent and prompt customer support, which efficiently handles user issues. Amazon Neptune is optimized for graph database deployment with efficient setup tools for relational data graphs. However, users might face delays in customer service responses. The critical difference lies in Azure’s ease across regions and consistent support compared to Neptune's efficiency in graph deployments.

Pricing and ROI: Azure Cosmos DB employs a pricing model based on provisioned throughput, scaling according to workload demands and offering significant ROI, especially for extensive global applications. Amazon Neptune presents competitive pricing for graph workloads but might incur higher costs with increased complexity due to its pricing structure based on graph compute units. Azure supports flexible use cases with its versatile cost structure, while Neptune remains cost-effective for specialized graph data applications.

To learn more, read our detailed Amazon Neptune vs. Microsoft Azure Cosmos DB Report (Updated: March 2026).

Buyer's Guide

Amazon Neptune vs. Microsoft Azure Cosmos DB

March 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 Neptune

Ranking in Managed NoSQL Databases

9th

Average Rating

8.6

Reviews Sentiment

4.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Microsoft Azure Cosmos DB

Ranking in Managed NoSQL Databases

1st

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

109

Ranking in other categories

Database as a Service (DBaaS) (4th), NoSQL Databases (2nd), Vector Databases (1st)

Mindshare comparison

As of March 2026, in the Managed NoSQL Databases category, the mindshare of Amazon Neptune is 6.9%, down from 13.8% compared to the previous year. The mindshare of Microsoft Azure Cosmos DB is 16.0%, down from 16.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Managed NoSQL Databases Mindshare Distribution
Product	Mindshare (%)
Microsoft Azure Cosmos DB	16.0%
Amazon Neptune	6.9%
Other	77.1%

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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reviewer2724105

Senior Director of Product Management at a tech vendor with 1,001-5,000 employees

Provides super sharp latency, excellent availability, and the ability to effectively manage costs across different tenants

For integrating Microsoft Azure Cosmos DB with other Azure products or other products, there are a couple of challenges with the current system. Right now, the vectors are stored as floating-point numbers within the NoSQL document, which makes them inefficiently large. This leads to increased storage space requirements, and searching through a vast number of documents in the vector database becomes quite costly in terms of RUs. While the integration works well, the expense associated with it is relatively high. I would really like to see a reduction in costs for their vector search, as it is currently on the expensive side. The areas for improvement in Microsoft Azure Cosmos DB are vector pricing and vector indexing patterns, which are unintuitive and not well described. I would also like to see the parameters of Fleet Spaces made more powerful, as currently, it's somewhat lightweight. I believe they've made those changes intentionally to better understand the cost model. However, we would like to take a more aggressive approach in using it. One of the most frustrating aspects of Microsoft Azure Cosmos DB right now is that you can only store one vector per document. Additionally, you must specify the configuration of that vector when you create an instance of Microsoft Azure Cosmos DB. Once the database is set up, you can't change the vector configuration, which is incredibly limiting for experimentation. You want the ability to try different settings and see how they perform, as there are numerous use cases for storing more than one vector in a document. While interoperability within the vector database is acceptable—for example, I can search for vectors—I still desire a richer set of configuration options.

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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."

"Microsoft Azure Cosmos DB has reduced our total cost of ownership by about half, allowing us to sell our product for about half of what we were selling it before, and Microsoft Azure Cosmos DB is probably 70% of the reason why that's true."

"rate Azure support nine out of 10. They respond quickly and will help you manage costs. However, they mainly give you an overview of the issue, so they'll never have an in-depth idea of what you're doing. They aren't the owners of our product, so they don't know much about it, but they can ask you generally: What are you doing? Are you doing too many updates? How can we reduce the cost?"

"The solution is used because we get faster response times with large data sets than with SQL. It's essential for us because we have half a billion rows, and we need to return them quickly."

"The value that it has added to my AI or search workloads is that I think it's optimized that process and made it easier; we have a lot of unstructured data coming from different dissimilar systems and different data sources, so correlating those things together and making sense of it has been very beneficial."

"It's highly scalable and supports consistency, security, and multiple security options."

"What I appreciate most are the latency and the access, which are guaranteed by the tool, which is really impressive."

"Reading and inserting data into Microsoft Azure Cosmos DB is a very smooth process."

"It gives us a lot of flexibility. The scaling is instantaneous as well. You immediately have all the resources available."

More Microsoft Azure Cosmos DB pros

Cons

"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."

"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."

"It should offer a simple user interface for querying Microsoft Azure Cosmos DB."

"Cosmos DB should continue evolving in AI features. We expect Cosmos DB to lead on that. There is potential for improved security features, which is important for data storage, especially for Dell Technologies. We must ensure data security remains the top priority."

"The size of the continuation token in Azure Cosmos DB should be static rather than increasing with more data, as it can lead to application crashes."

"It would be ideal if we could integrate Cosmos DB with our Databricks. At this point, that's not possible."

"Because there is no local way of doing things, Azure Cosmos DB will always be considered expensive."

"While Microsoft Azure Cosmos DB is generally easy to use, it has some limitations."

"There aren't any specific areas that need improvement, but if there were a way to achieve the right cosine similarity score without extensive testing, that would be very beneficial."

"A limitation in Azure Cosmos DB is the 2 MB document size. Developers need more systemic support in chaining multiple documents if more than 2 MB is required."

More Microsoft Azure Cosmos DB cons

Pricing and Cost Advice

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

"The pricing is perceived as being on the higher side. However, if you have large data operations, it might reduce costs due to performance efficiencies."

"Microsoft provides fair pricing."

"Microsoft Azure Cosmos DB's licensing costs are monthly."

"Cosmos DB is a highly cost-optimized solution when used correctly."

"Our experience with the pricing and setup cost is that it aligns with what we expect based on the pricing we see. However, I would absolutely like it to be less if possible."

"I would rate Cosmos DB's cost at seven out of ten, with ten being the highest."

"Right now, I have opted for the student subscription plan, for which Microsoft charges me around 100 USD. The pricing of the solution depends on the solution's usage."

"Pricing is mid- to high-end."

More Microsoft Azure Cosmos DB pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

21%

University

14%

Computer Software Company

11%

Insurance Company

Legal Firm

12%

Financial Services Firm

10%

Comms Service Provider

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	33
Midsize Enterprise	22
Large Enterprise	58

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 do you like most about Microsoft Azure Cosmos DB?

The initial setup is simple and straightforward. You can set up a Cosmos DB in a day, even configuring things like availability zones around the world.

See all answers

What is your experience regarding pricing and costs for Microsoft Azure Cosmos DB?

Microsoft Azure Cosmos DB's pricing model has aligned with my budget expectations because I can tune the RU as I need to, which helps a lot. Microsoft Azure Cosmos DB's dynamic auto-scale or server...

See all answers

What needs improvement with Microsoft Azure Cosmos DB?

I have not utilized Microsoft Azure Cosmos DB multi-model support for handling diverse data types. I'm not in the position to decide if clients will use Microsoft Azure Cosmos DB or any other datab...

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Comparisons

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MongoDB Atlas vs Amazon Neptune

Compared 20% of the time

Amazon DynamoDB vs Amazon Neptune

Compared 11% of the time

Amazon DocumentDB vs Amazon Neptune

Compared 8% of the time

Amazon Timestream vs Amazon Neptune

Compared 8% of the time

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Pinecone vs Microsoft Azure Cosmos DB

Compared 6% of the time

Amazon DynamoDB vs Microsoft Azure Cosmos DB

Compared 6% of the time

MongoDB Atlas vs Microsoft Azure Cosmos DB

Compared 5% of the time

MongoDB Enterprise Advanced vs Microsoft Azure Cosmos DB

Compared 5% of the time

Neo4j AuraDB vs Microsoft Azure Cosmos DB

Compared 3% of the time

More Microsoft Azure Cosmos DB Competitors

Product Reports

Buyer's Guide

Amazon Neptune

March 2026

Download Amazon Neptune product report

Buyer's Guide

Microsoft Azure Cosmos DB

March 2026

Download Microsoft Azure Cosmos DB product report

Also Known As

No data available

Microsoft Azure DocumentDB, MS Azure Cosmos DB

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)

Microsoft Azure Cosmos DB offers scalable, geo-replicated, multi-model support with high performance and low latency. It provides seamless Microsoft service integration, benefiting those needing flexible NoSQL, real-time analytics, and automatic scaling for diverse data types and quick global access.

Azure Cosmos DB is designed to store, manage, and query large volumes of both unstructured and structured data. Its NoSQL capabilities and global distribution are leveraged by organizations to support activities like IoT data management, business intelligence, and backend databases for web and mobile applications. While its robust security measures and availability are strengths, there are areas for improvement such as query complexity, integration with services like Databricks and MongoDB, documentation clarity, and performance issues. Enhancements in real-time analytics, API compatibility, cross-container joins, and indexing capabilities are sought after. Cost management, optimization tools, and better support for local development also require attention, as do improvements in user interface and advanced AI integration.

What are the key features of Azure Cosmos DB?

Scalability: Effortlessly handles scaling for large workloads.
Geo-replication: Provides global data access with low latency.
Multi-model Support: Compatible with diverse data types.
NoSQL Flexibility: Offers a non-relational database experience.
Real-time Analytics: Facilitates data-driven decision-making.
Automation: Simplifies scaling and maintenance processes.

What benefits can users expect from Cosmos DB?

High Performance: Ensures rapid processing and low latency.
Ease of Use: Features a user-friendly interface enhancing deployment speed.
Seamless Integration: Connects effortlessly with Microsoft services.
Security: Offers robust measures to protect data integrity.
Consistent Availability: Ensures continuous access to data worldwide.

Industries use Azure Cosmos DB to support business intelligence and IoT data management, using its capabilities for backend databases in web and mobile applications. The platform's scalability and real-time analytics benefit sectors like finance, healthcare, and retail, where managing diverse datasets efficiently is critical.

Microsoft

Sample Customers

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

TomTom, KPMG Australia, Bosch, ASOS, Mercedes Benz, NBA, Zero Friction, Nederlandse Spoorwegen, Kinectify

Buyer's Guide

Amazon Neptune vs. Microsoft Azure Cosmos DB

March 2026

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