Not just because of it being NoSQL, but because all of the support I find in the NodeJS community through packages and utilities that make it dead easy to use it for several use-cases. Now-a-days, I really found my solution in Mongo. One of the main challenges with analyzing a NoSQL database being familiar in the SQL ways, is that it's easy to look for 'analogies' for what makes SQL useful, like relationship enforcing, transactions and the cascading effect on deletes, updates and inserts, and that limit your vision a lot when analyzing a tool like Mongo, especially in a micro-services pattern. However, frankly, I didn't want to model statically all data, since I have several distinct schemas (like for different product types) and I wanted some flexibility to add or remove as I saw fit. See moreĪ few months ago, I had decided to use Postgres because since its version 9 it showed a lot of progress for being a high-availability database. It feels like you have most experience with SQL/RDBMS technologies, so for the simplest learning curve, and if your application fits it, then I'd personally start by looking at AWS Aurora. RDBMS/SQL stores are great for having as many indexes as you want, other than the slow-down in write speed, whereas databases like Amazon DynamoDB provide blisteringly fast read/write performance, but are very limited on key indexing capabilities. MongoDB, with its document-store type solution is a very different model to key-value-pair stores (like AWS DynamoDB), or column stores (like AWS RedShift) or for more complex data relationships, Entity Graph Stores (like AWS Neptune), to stores designed for tokenisation and text search (ElasticSearch) etc.Īlso critical in all this is how many items you believe you need to index by. however please don't fall into the trap of considering 'NoSQL' as being single category. Your question regards 'Relational or not' is obviously key, and you need to consider both your required data structure, as well as the ACID requirements of your application model, as well as the non-functional requirements in terms of scalability, resilience, whether you want security authorisation at the highest application tier, or right down to 'row' level in the database, etc. Particularly if you are planning to host in either AWS or Azure, then your first point of call should be the PaaS (Platform as a Service) databases supplied by these vendors, as you will find yourself requiring a lot less effort to support them, much easier Disaster Recovery options, and also, depending on how PAYG the database is that you use, potentially also much cheaper costs than having a dedicated database server.

The most important question is where are you planning to host? On-premise, or in the cloud. MongoDB has a broader approval, being mentioned in 2175 company stacks & 2143 developers stacks compared to Neo4j, which is listed in 114 company stacks and 47 developer stacks. Lyft, MIT, and are some of the popular companies that use MongoDB, whereas Neo4j is used by Movielala, Hinge, and Sportsy. It seems that MongoDB with 16.2K GitHub stars and 4.08K forks on GitHub has more adoption than Neo4j with 6.56K GitHub stars and 1.62K GitHub forks. MongoDB and Neo4j are both open source tools. 'Document-oriented storage' is the primary reason why developers consider MongoDB over the competitors, whereas 'Cypher – graph query language' was stated as the key factor in picking Neo4j. MongoDB belongs to 'Databases' category of the tech stack, while Neo4j can be primarily classified under 'Graph Databases'. 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. Neo4j stores data in nodes connected by directed, typed relationships with properties on both, also known as a Property Graph. What is Neo4j? The world’s leading Graph Database. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding. MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. What is MongoDB? The database for giant ideas.

MongoDB vs Neo4j: What are the differences?

Atach to arangodb docker conainer