Likelihood to Recommend If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
Read full review Titan is definitely a good choice, but it has its learning curve. The documentation may lack in places, and you might have to muster answers from different sources and technologies. But at its core, it does the job of storing and querying graph databases really well. Remember that titan itself is not the whole component, but utilizes other technologies like cassandra, gremlin, tinkerpop, etc to do many other things, and each of them has a learning curve. I would recommend titan for a team, but not for a single person. For single developer, go with
Neo4j .
Read full review Pros Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet. Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management. Read full review Titan is really good for abstraction of underlying infrastructure. You can choose between different storage engine of your choice. Open source, backed by community, and free. Supports tinkerpop stack which is backed by apache. Uses gremlin for query language making the whole query structure standardized and open for extension if another graph database comes along in future. Read full review Cons An aggregate pipeline can be a bit overwhelming as a newcomer. There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close. Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty. Read full review The community is lacking deep documentation. I had to spend many nights trying to figure many things on my own. As graph databases will grow popular, I am sure this will be improved. Not enough community support. Even in SO you might not find many questions. Though there are some users in SO who quickly answer graph database questions. Need more support. Would love an official docker image. Read full review Likelihood to Renew I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
Read full review Usability NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
Read full review Support Rating Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
Read full review Implementation Rating While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
Tom Maiaroto Sr. Platform Developer / UX Designer / Optimization Engineer
Read full review Alternatives Considered We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need
Cassandra .
Cassandra 's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation;
Cassandra provides native Hadoop support.
Read full review To be honest, titan is not as popular as
Neo4j , though they do the same thing. In my personal opinion, titan has lot of potential, but
Neo4j is easier to use. If the organization is big enough, it might choose titan because of its open source nature, and high scalability, but
Neo4j comes with a lot of enterprise and community support, better query, better documentation, better instructions, and is also backed by leading tech companies. But titan is very strong when you consider standards. Titan follows gremlin and tinkerpop, both of which will be huge in future as more graph database vendors join the market. If things go really well, maybe
Neo4j might have to support gremlin as well.
Read full review Return on Investment Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models) You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB Read full review Steep learning curve. Your engineers would have to spend lots of time learning different components before they feel comfortable. Have to plan ahead. Maybe this is the nature of graph databases, but I found it difficult to change my schemas after I had data in production. It is free, so time is the only resource you have to put in titan. Read full review ScreenShots