Google Cloud Datastore vs. Neo4j

If you want a serverless NoSQL database, no matter it is for personal use, or for company use, Google Cloud Datastore should be on top of your list, especially if you are using Google Cloud as your primary cloud platform. It integrates with all services in the Google Cloud platform.

Incentivized

Neo4J is great for creating network graphs or illustrating how things are related. It is also good for finding individuals or things that have greater influence than others in a system. It is not appropriate if you have standard data sets that can be analyzed using conventional methods or visualized using Tableau, for example.

Incentivized

• Automatically handles shards and replication.
• Schema-less & NoSQL.
• Fully managed.

Incentivized

• Mature Query language, I found Cypher QL to be mature in handling all sorts of problems we throw at it. Its expressive enough to be intuitive while providing rich features for various scenarios.
• Native support for REST API, that makes interacting with Neo4J intuitive and easy.
• Support for Procedures in Java, procedures are custom code that could be added to the Neo4J to write custom querying of data. The best part about the procedures is it could be invoked using the REST API. This allows us to overcome any shortcomings from their Cypher query language.
• Nice UI and interface for executing the Query and visualizing the response.
• UI access controlled by User credentials allows for neat access controls.
• Awesome free community edition for small-scale projects.

Incentivized

• It is hosted on GCP, which makes it harder if your company have multi-cloud strategy.
• When you want to migrate to other cloud providers, there can be a caveat.

Incentivized

• One of the hardest challenges that Neo4j had to solve was the horizontal scaling problem. I am not updated on recent developments, but at the time of my use, I couldn't find a viable solution.
• Neo4j does not play with other open source APIs like Blueprint. You have to use the native Neo4j API.
• There wasn't a visual tool to see your data. Of course, third party tools are always available, but I would have loved something which came with the Neo4j bundle. I love that Docker comes bundled with Kitematic, so it's not wrong to hope that Neo4j could also ship with some default visualization software.

Incentivized

For the amount of use we're getting from Google Cloud Datastore, switching to any other platform would have more cost with little gain. Not having to manage and maintain Google Cloud Datastore for over 4 years has allowed our teams to work on other things. The price is so low that almost any other option for our needs would be far more expensive in time and money.

Incentivized

[Based on] Query Language, Performance on small and large data sets, integration and deployment, analysis, API support, Interactive UI.

Incentivized

We selected Google Cloud Datastore as one of our candidates for our NoSQL data is because it is provided by Google Cloud, which fits our needs. Most of our infrastructure is on Google Cloud, so when we think about the NoSQL database, the first thing we thought about is Google Cloud Datastore. And it proves itself.

Incentivized

Neo4j is a graph store and has different use cases compared to another NoSQL Document store like MongoDB. MongoDB is a bad choice when joins are common as existing operators for joining two documents (similar to tables in a relational store) as Mongo 3.5 use SQL like join algorithms which are expensive. MongoDB is a great choice when distributed schemaless rich document structures are important requirements. Cross document transaction support is not native to MongoDB yet, whereas Neo4J is ACID complaint with all its operations.

Incentivized

• Simple billing part of Google Cloud Platform
• No time spent configuring and maintaining Google Cloud Datastore.
• Very good uptime for our applications.

Incentivized

• Positive: Less complex queries on graph structures, than in relational databases.
• Negative: maintenance is a huge deal, things doesn't work and break, requiring lengthy restore operations.