Amazon Timestream 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 #6 with an average rating of 9.0, while Neo4j is ranked #8 with an average rating of 8.9. Amazon Web Services (AWS) holds a 6.2% 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 Timestream

Read 5 Amazon Timestream reviews

622 Views
622 Comparison Views

100% willing to recommend

Neo4j AuraDB

Read 7 Neo4j AuraDB reviews

539 Views
539 Comparison Views

100% willing to recommend

Amazon Timestream

Neo4j AuraDB

Comparison Buyer's Guide

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Executive SummaryUpdated on Mar 3, 2025

Amazon Timestream and Neo4j AuraDB are competing in the database solutions category. Timestream has the upper hand with its pricing and integration capabilities, while Neo4j AuraDB stands out for its advanced graph analysis features.

Features: Amazon Timestream is maintenance-free, customizable, and offers real-time data handling. It is easy to collect and store data and provides fast, scalable database management. Neo4j AuraDB offers easy integration with multiple languages like Python and supports complex graph analytics. It has flexible data models, broad language support, and provides excellent graph database services in the cloud.

Room for Improvement: Amazon Timestream could improve its data management capabilities and offer more options beyond time-series data. Its interface could be enhanced for better user interaction and integration with non-AWS environments. Neo4j AuraDB may enhance its scaling capabilities for large data sets and improve the ease of assigning accuracy metrics in graph analytics. The integration with non-cloud environments could also be better.

Ease of Deployment and Customer Service: Amazon Timestream offers seamless integration within the AWS ecosystem, providing easy deployment and strong customer support. Neo4j AuraDB also emphasizes straightforward deployment with fast provisioning and automated updates. Timestream holds an advantage in environments already within AWS, while Neo4j AuraDB provides comprehensive support across multiple cloud platforms.

Pricing and ROI: Amazon Timestream is cost-effective for time-series applications and offers a good ROI for its specific strengths. Neo4j AuraDB has a pricing model reflecting its feature-rich offerings, suitable for complex analytics tasks. Although Neo4j AuraDB may have higher initial costs, it offers comprehensive analytics benefits that justify the expense. Timestream is more cost-effective for straightforward time-series analysis, and AuraDB provides better ROI for detailed graph analytics.

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

Buyer's Guide

Amazon Timestream 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 Timestream

Ranking in Managed NoSQL Databases

6th

Average Rating

9.0

Reviews Sentiment

6.9

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 Timestream is 6.2%, down from 11.0% 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 Timestream	6.2%
Neo4j AuraDB	5.2%
Other	88.6%

Managed NoSQL Databases

Featured Reviews

Sushil Pandey

Data Engineer at Tiger Analytics

It is helpful to get telemetry data from the devices in real-time

It is an easily scalable solution. When it comes to the retention period, if someone wants to change, they have to define it at the start. Later on, if users want to change it again, like, or increase the retention policy, then they have to create the table again and do so, and if it is not done, then we face problems. It will increase the retention, but when you try to insert a record or an older record that is not included in the range of your retention period, then you can face some problems and, like, it will throw some errors. The tool is scalable, but it should be defined at the start as to how much retention you want. For scalability, I rate the tool a six or seven out of ten.

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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

"The best things about Amazon Timestream are it's maintenance-free, customizable, and has no lag issues. It's always real-time."

"You can quickly aggregate data from the last ten years with Amazon Timestream."

"What I like best is that the tool is easy to collect and store data and is fast and scalable. The fully managed database is easy to understand."

"Using Amazon Timestream has been seamless due to its integration within the AWS ecosystem and ease of use for the engineering team."

"If you drop a message, the solution's technical support will definitely reply."

"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."

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

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

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

"The tool is easy to use."

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

Cons

"Arranging the database schema is a bit challenging."

"The solution could be improved by making it easier for new graduates like me to use. Better explanations of queries and how to use them with other AWS services would help."

"The tool could be improved by increasing the batch size from one hundred records to five hundred or a thousand to speed up indexing."

"There are disadvantages when it comes to time series databases since you can't delete anything from Amazon Timestream data."

"There are certain features that we would like to see added and we are collaborating with the product teams on these areas."

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

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

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

"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."

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

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

Pricing and Cost Advice

"For 1GB of data, the solution charges $ 0.01 in the US region."

"We pay over $10 million a year to Amazon."

"Amazon Timestream's pricing seems manageable to me."

"We don't see high costs with Amazon Timestream, which may vary by company."

"I used the free tier."

"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."

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Top Industries

By visitors reading reviews

Computer Software Company

19%

Manufacturing Company

11%

Insurance Company

Outsourcing Company

Computer Software Company

32%

Educational Organization

10%

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 Timestream?

Amazon Timestream's pricing seems manageable to me.

See all answers

What needs improvement with Amazon Timestream?

We are working on a few open change requests with the engineering teams on AWS's side. There are certain features that we would like to see added and we are collaborating with the product teams on ...

See all answers

What is your primary use case for Amazon Timestream?

We use Amazon Timestream as a data historian for IT data. It stores all individual measurements of our customers' IoT devices for a certain period of time, allowing them to perform time-series-base...

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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...

See all answers

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 ...

See all answers

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Compared 25% of the time

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Product Reports

Buyer's Guide

Managed NoSQL Databases

September 2025

Download Amazon Timestream product report

Buyer's Guide

Neo4j AuraDB

September 2025

Download Neo4j AuraDB product report

Overview

Amazon Timestream offers a fully managed, maintenance-free database designed specifically for time series data management, characterized by simplicity, speed, and scalability for handling real-time operations.

Amazon Timestream provides a powerful solution for managing time series data by enabling users to aggregate decades of data quickly and merge updates seamlessly. It excels in simplicity, speed, and scalability, making it an ideal choice for real-time analytics and IoT data storage. Despite its benefits, there's room for improvement in query explanations and integration with other AWS services. Enhancements in data indexing, batch limits, cost management, and schema arrangement are ongoing efforts to better serve its users.

What are the key features of Amazon Timestream?

Real-time Operations: Provides lag-free data management.
Maintenance-Free: No manual work required for setup or upkeep.
Scalability: Handles vast datasets efficiently.
Customizable: Easily adapts to specific business needs.
Fully Managed: Reduces the complexity of database management.

What benefits should users look for in reviews?

Operational Efficiency: Improved productivity with automated processes.
Simplified Data Management: Easy data merging without additional actions.
Cost Management: Monitoring data costs effectively.
Ease of Integration: Works seamlessly with other tools.

Industries implement Amazon Timestream to automate real-time analytics and manage IoT telemetry data. In microgrid solar projects, it aids in assessing safety and charge states, while in IoT networks, it serves as a comprehensive data historian for device data analysis, enhancing decision-making and operational efficiency.

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

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers

Information Not Available

Buyer's Guide

Amazon Timestream vs. Neo4j AuraDB

September 2025

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