
Overview

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For our fully managed offer, visit our Neo4j AuraDB Professional (Pay-as-You-Go) listing: https://aws.amazon.com/marketplace/pp/prodview-2t3o7mnw5ypee
Neo4j AuraDB is a fast, reliable, scalable and completely automated graph database-as-a-service for connected data. AuraDB lets you focus on developing rich, graph-powered applications, without any administration hassle. Built on the world's most trusted graph platform, AuraDB enables lightning-fast queries and real-time insights powering connected data use cases such as fraud detection, recommendations, knowledge graphs and customer 360.
Zero administration: Provision in minutes, scale on-demand, automated service upgrades, no maintenance window ever. Available in all regions.
Enterprise-grade security and privacy: Offers end-to-end data encryption, VPC isolation with dedicated infrastructure (depending on plan) and advanced role-based access control with granular database security. AuraDB is GDPR and CCPA compliant.
99.95% Availability SLA: Built on self-healing architecture with multi-AZ distributed cluster, AuraDB guarantees high availability without service interruption. AuraDB is ACID compliant and includes fully managed backups for robust data availability.
Rich developer toolkit: Flexible property graph data model with support for Cypher, the easy and powerful graph query language and GraphQL. Built in tools for graph visualization, monitoring and powerful procedures to extend functionality.
Simple pricing: Transparent capacity-based consumption pricing.
For private offers or other needs, please contact marketplace-sales@neo4j.com
Highlights
- Fully-managed graph database-as-a-service supporting flexible property graph data model and Cypher query language
- Role-based access control with granular schema-based security and VPC isolation (depending on plan)
- 99.95% uptime guarantee with fault-tolerant architecture and automated backups
Details
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Financing for AWS Marketplace purchases
Pricing
Dimension | Description | Cost/12 months |
---|---|---|
AuraDB Virtual Dedicated Cloud | AuraDB Virtual Dedicated Cloud 32 GB of Memory Capacity Reservation | $91,104.00 |
AuraDB Business Critical | AuraDB Business Critical 16 GB of Memory Capacity Reservation | $28,032.00 |
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All fees are non-cancellable and non-refundable except as required by law.
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Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
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24x7 support is included with your subscription. Please refer to https://neo4j.com/terms/support-terms/aura/ for more information.
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AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Customer reviews
Neo4j Turns Historical Data into a Queryable Knowledge Graph
This makes querying for complex patterns, like finding all artists who influenced a particular art movement or tracing the exhibitions of a certain artwork across different places, efficient and straightforward.
What are the main points that like it more about:
- That Neo4j optimizes queries for traversing relationships, such as "What art pieces were created by artists in a specific location?" which make the response faster than in traditional relational databases.
- We like that you can easily expand the graph with new relationships or attributes as your dataset grows.
- Also, we can search deeper in our data, finding more meaningful connections between our historical data, like trends in art styles or how artists influenced each other across regions, or the several relationship of multiple artist for a specific location or art
The flexibility and performance of graph-based queries really shine when dealing with highly relational data, like historical and cultural information.
- First big issue was about the restoring the old data from a different version of the database. Neo4j’s backup and restore processes are more complex compared to traditional relational databases. Maintaining backups for our history app can be a bit challenging, especially with the extensive and interconnected historical data which we are managing. As our dataset grows, ensuring that all this valuable information is securely backed up can require careful planning and additional effort.
- Different query language than traditional ones. Neo4j uses Cypher, which is different than traditional and may require time to learn especially if you're coming from a SQL background like I did. For more complex queries involving relationships between artists, artworks, places, and tags, Cypher syntax can become difficult to manage, especially as the graph structure grows more intricate, you need to optimize the query to not allow a lot of memory time in the whole process results
- Also, one more thing that we find of is importing data into Neo4j, especially from structured sources like Wiki pages, can be more complex than with traditional relational databases. The data needs to be transformed into a graph-friendly format, which can add a layer of complexity when dealing with large-scale imports or frequent updates from sources like Wiki.
- First is how efficiently managing big and comples relationships: Neo4j excels at handling complex, highly interconnected data. In our app, each piece of art may be related to multiple artists, places, and historical contexts. Traditional relational databases struggle with deeply nested relationships, often requiring complex joins and leading to slow queries. Neo4j, however, is designed for querying relationships directly, allowing you to quickly find connections between entities like "artworks created by artists in specific places" or "artists influenced by others across time." What is the benefit for our app can offer fast and accurate search results, even with intricate historical data relationships, improving user experience.
- Flexible of the structure for our data: As our dataset grows and evolves day by day, Neo4j allows us to easily expand our graph by adding new nodes (e.g., new artists or art types) or relationships (e.g., "influenced by" or "exhibited at"). In a historical context, new discoveries or data sources (e.g., additional Wiki information) can be easily integrated without restructuring the entire database. The main thing is that the app remains scalable and adaptable, accommodating future data changes without major disruptions.
- Relationships Searching: One thing that Neo4j has ability to search deeper, contextual connections. users might want to explore how specific art movements spread geographically, or how one artist's work related to others across different periods or regions. Neo4j allows us to surface these non-obvious patterns easily, providing richer, more valuable insights to users.
- Performance: As our app will grow up in the amount of stored historical data, maintaining query performance can be challenging. Neo4j is optimized for traversing vast networks of nodes and relationships efficiently, making it ideal for large-scale, relationship-driven queries.
Neo4j used for design supply chain solutions
Neo4j Review: A Great Database to Start with Graph Technologies
Open source and community edition that can be self-hosted.
Neo4j Browser to visualize graph data.
Best Graph Database for your data pattern insight and ML workload
Match (p: Person { Gender:"Male"} ) return p )
Neo4j's Browser and Bloom feature gives business stakeholder and data scientist/analyst to analyze their data which i think currently no other database give at this moment
and on top of that they have their own graph data science library which gives feasibility in developing application such as link prediction, recommendation system, chatbots