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Amazon DynamoDB vs Neo4j: What are the differences?
Amazon DynamoDB and Neo4j are both highly popular and widely used NoSQL databases, but they differ in their core functionality and design. Here are the key differences between Amazon DynamoDB and Neo4j:
Data Model: Amazon DynamoDB is a document-based NoSQL database, meaning it stores structured data in JSON-like documents. It offers a key-value model with optional secondary indexes. On the other hand, Neo4j is a graph database that represents data as nodes, relationships between nodes, and properties associated with nodes and relationships. It enables high-performance graph traversal and complex querying.
Querying Abilities: DynamoDB offers simple querying capabilities using primary keys and secondary indexes. It supports basic CRUD operations and can perform range queries on numeric and string attributes. In contrast, Neo4j provides powerful graph querying capabilities that allow traversing complex relationships and patterns. It supports graph-oriented queries to find paths, shortest paths, common nodes, and more.
Scalability: DynamoDB is a fully managed, highly scalable database that automatically scales horizontally without downtime. It can handle large volumes of traffic and offer low latency with automatic data replication across multiple availability zones. Neo4j, on the other hand, is designed to work on a single server or cluster and requires manual scaling to handle high loads.
ACID Compliance: DynamoDB ensures Atomicity, Consistency, Isolation, and Durability (ACID) properties only within a single partition or item. It does not guarantee ACID across multiple partitions or items. On the other hand, Neo4j offers transactional consistency on a global scale, allowing ACID operations across the entire dataset.
Data Relationships: DynamoDB does not have built-in support for relationships between different items. It is primarily designed for key-value data storage. In contrast, Neo4j's graph database model is specifically designed to handle complex relationships between entities. It allows developers to define relationships between nodes and perform efficient queries based on those relationships.
Use Cases: Due to its document-based structure, DynamoDB is suitable for applications with predominantly read-heavy workloads and simple data access patterns. It is commonly used for real-time applications, gaming, and content management systems. Neo4j, with its graph database capabilities, is ideal for applications that heavily rely on analyzing and querying complex relationships, such as social networks, fraud detection, recommendation systems, and knowledge graphs.
In Summary, Amazon DynamoDB is a scalable, document-based NoSQL database with key-value storage, while Neo4j is a powerful graph database with extensive graph querying capabilities and support for relationships. DynamoDB is suitable for read-heavy workloads and simple data access patterns, whereas Neo4j excels in applications with complex relationship analysis and querying requirements.
Hi, I want to create a social network for students, and I was wondering which of these three Oriented Graph DB's would you recommend. I plan to implement machine learning algorithms such as k-means and others to give recommendations and some basic data analyses; also, everything is going to be hosted in the cloud, so I expect the DB to be hosted there. I want the queries to be as fast as possible, and I like good tools to monitor my data. I would appreciate any recommendations or thoughts.
Context:
I released the MVP 6 months ago and got almost 600 users just from my university in Colombia, But now I want to expand it all over my country. I am expecting more or less 20000 users.
I have not used the others but I agree, ArangoDB should meet your needs. If you have worked with RDBMS and SQL before Arango will be a easy transition. AQL is simple yet powerful and deployment can be as small or large as you need. I love the fact that for my local development I can run it as docker container as part of my project and for production I can have multiple machines in a cluster. The project is also under active development and with the latest round of funding I feel comfortable that it will be around a while.
Hi Jaime. I've worked with Neo4j and ArangoDB for a few years and for me, I prefer to use ArangoDB because its query sintax (AQL) is easier. I've built a network topology with both databases and now ArangoDB is the databases for that network topology. Also, ArangoDB has ArangoML that maybe can help you with your recommendation algorithims.
Hi Jaime, I work with Arango for about 3 years quite a lot. Before I do some investigation and choose ArangoDB against Neo4j due to multi-type DB, speed, and also clustering (but we do not use it now). Now we have RMDB and Graph working together. As others said, AQL is quite easy, but u can use some of the drivers like Java Spring, that get you to another level.. If you prefer more copy-paste with little rework, perhaps Neo4j can do the job for you, because there is a bigger community around it.. But I have to solve some issues with the ArangoDB community and its also fast. So I will preffere ArangoDB... Btw, there is a super easy Foxx Microservice tool on Arango that can help you solve basic things faster than write down robust BackEnd.
We are building a social media app, where users will post images, like their post, and make friends based on their interest. We are currently using Cloud Firestore and Firebase Realtime Database. We are looking for another database like Amazon DynamoDB; how much this decision can be efficient in terms of pricing and overhead?
Hi, Akash,
I wouldn't make this decision without lots more information. Cloud Firestore has a much richer metamodel (document-oriented) than Dynamo (key-value), and Dynamo seems to be particularly restrictive. That is why it is so fast. There are many needs in most applications to get lightning access to the members of a set, one set at a time. Dynamo DB is a great choice. But, social media applications generally need to be able to make long traverses across a graph. While you can make almost any metamodel act like another one, with your own custom layers on top of it, or just by writing a lot more code, it's a long way around to do that with simple key-value sets. It's hard enough to traverse across networks of collections in a document-oriented database. So, if you are moving, I think a graph-oriented database like Amazon Neptune, or, if you might want built-in reasoning, Allegro or Ontotext, would take the least programming, which is where the most cost and bugs can be avoided. Also, managed systems are also less costly in terms of people's time and system errors. It's easier to measure the costs of managed systems, so they are often seen as more costly.
Pros of Amazon DynamoDB
- Predictable performance and cost62
- Scalable56
- Native JSON Support35
- AWS Free Tier21
- Fast7
- No sql3
- To store data3
- Serverless2
- No Stored procedures is GOOD2
- ORM with DynamoDBMapper1
- Elastic Scalability using on-demand mode1
- Elastic Scalability using autoscaling1
- DynamoDB Stream1
Pros of Neo4j
- Cypher – graph query language70
- Great graphdb61
- Open source33
- Rest api31
- High-Performance Native API27
- ACID23
- Easy setup21
- Great support17
- Clustering11
- Hot Backups9
- Great Web Admin UI8
- Powerful, flexible data model7
- Mature7
- Embeddable6
- Easy to Use and Model5
- Best Graphdb4
- Highly-available4
- It's awesome, I wanted to try it2
- Great onboarding process2
- Great query language and built in data browser2
- Used by Crunchbase2
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Cons of Amazon DynamoDB
- Only sequential access for paginate data4
- Scaling1
- Document Limit Size1
Cons of Neo4j
- Comparably slow9
- Can't store a vertex as JSON4
- Doesn't have a managed cloud service at low cost1
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