Google Cloud Datastore vs. Neo4j

Using Google Cloud Datastore in conjunction with Google AppEngine was a very seamless integration and much easier than using other datastores since so much of the configuration is abstracted for you. Because of this, creating simple applications is very easy and getting Google Cloud Datastore to power the backend ties everything together. If we were using Google Compute Engine, I'd imagine the same seamless experience would be there as well.

Incentivized

Its very well suited for storing graph types relationship information, such as a group of people and their relationships. Data modeling this sort of information in a traditional SQL database is a pain and inefficient. Using Neo4J allows for efficient modeling of data while providing rich querying capabilities using Cypher. Its also a great fit for any programming language because of its support for REST API. It's less appropriate for any other data structure other than Graph data. So as with any DB, evaluate the data structure and query and if the querying revolves around relationships, then Neo4J is a fit. If there is more need for looking up individual nodes and their associated information, Neo4J might not be the most efficient solution in the market.

Incentivized

• It is hosted in GCP, our primary cloud provider.
• It integrates with all the services we use in GCP.

Incentivized

• When joins are a common in a relational store, switching to Neo4j is better
• When pattern matching and surfacing interesting insights is the goal, neo4j's cypher is pretty powerful
• When schema is not completely known beforehand and needs to be evolved with time

Incentivized

• Part of the Google Cloud Platform walled garden.
• Pay for read/writes to the datastore, in addition to storage.
• Not many libraries exist.

Incentivized

• It would be nice to have some concept of namespaces, or some way of roughly making a single instance multi-tenant. It'd be nice to make sandboxing easier.
• Automatic backups could be improved.

Incentivized

I give Google Cloud a full score because it satisfies our needs so well. We host most of our infrastructure on Google Cloud and using Google Cloud Datastore helps us to solve our NoSQL storage problem. and Google Cloud Datastore is so scalable and elastic. It saves us lots of time to maintain and saves us 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

I have not used anything like Neo4J because of how unique it is in the work that it allows me to do. I am not aware of any other graph database platforms and it might be because it is a growing area (especially in the world of pharmaceuticals). I would be open to trying other softwares though.

Incentivized

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

Incentivized

• For experimentation purposes, it had a positive impact on my company. It was very natural to work with Neo4j and so intuitive to visualize the data.
• Neo4j community edition is free, which is what we experimented on. So there was no investment up front apart from employee's time. But this quickly gave results and it was time well spent.
• Neo4j is a cool but very new technology. It was hard to have people onboard, especially some of the leadership and relational folks.

Incentivized