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Neo4j vs PostGIS: What are the differences?
Neo4j: The world’s leading Graph Database. Neo4j stores data in nodes connected by directed, typed relationships with properties on both, also known as a Property Graph. It is a high performance graph store with all the features expected of a mature and robust database, like a friendly query language and ACID transactions; PostGIS: Open source spatial database. PostGIS is a spatial database extender for PostgreSQL object-relational database. It adds support for geographic objects allowing location queries to be run in SQL.
Neo4j belongs to "Graph Databases" category of the tech stack, while PostGIS can be primarily classified under "Database Tools".
Some of the features offered by Neo4j are:
- intuitive, using a graph model for data representation
- reliable, with full ACID transactions
- durable and fast, using a custom disk-based, native storage engine
On the other hand, PostGIS provides the following key features:
- Processing and analytic functions for both vector and raster data for splicing, dicing, morphing, reclassifying, and collecting/unioning with the power of SQL
- raster map algebra for fine-grained raster processing
- Spatial reprojection SQL callable functions for both vector and raster data
"Cypher – graph query language" is the top reason why over 55 developers like Neo4j, while over 22 developers mention "De facto GIS in SQL" as the leading cause for choosing PostGIS.
Neo4j and PostGIS are both open source tools. It seems that Neo4j with 6.56K GitHub stars and 1.62K forks on GitHub has more adoption than PostGIS with 636 GitHub stars and 242 GitHub forks.
According to the StackShare community, Neo4j has a broader approval, being mentioned in 114 company stacks & 47 developers stacks; compared to PostGIS, which is listed in 53 company stacks and 14 developer stacks.
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.
Pros of Neo4j
- Cypher – graph query language70
- Great graphdb61
- Open source33
- Rest api31
- High-Performance Native API27
- ACID24
- Easy setup21
- Great support17
- Clustering11
- Hot Backups9
- Great Web Admin UI8
- Mature7
- Powerful, flexible data model7
- Embeddable6
- Easy to Use and Model5
- Best Graphdb4
- Highly-available4
- Great onboarding process2
- It's awesome, I wanted to try it2
- Used by Crunchbase2
- Great query language and built in data browser2
Pros of PostGIS
- De facto GIS in SQL25
- Good Documentation5
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Cons of Neo4j
- Comparably slow9
- Can't store a vertex as JSON4
- Doesn't have a managed cloud service at low cost1
Cons of PostGIS
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