IBM IMS vs. InterSystems Caché (legacy product) vs. MongoDB

We have built a database of a network of bank branches with all the needs of security and recovery/restart. It requires knowledge of obsolete maintenance languages and perhaps it is too rigid in the schemes.

Incentivized

It's definitely great for medical industries that need the vast amounts of features/security/performance, however if you need something simple then this would be too much. There is a learning curve, and if you come from more common database technologies, then there will be a lot of differences to handle. Simple database needs would be better fulfilled elsewhere, but Cache is for when you need to take the next step, whether that be in the volume, complexity, or security of ETL.

Incentivized

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.

Incentivized

• Security
• Reliability
• Big volume of data and good performance

Incentivized

• Performance
• Robustness
• Reliable

Incentivized

• 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.

Incentivized

• Certainly, not being a DB relational penalizes its use
• It should be more flexible
• Open up to more recent languages

Incentivized

• The IDE IntelliSense needs to be improved.

Incentivized

• 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.

Incentivized

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.

Incentivized

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.

Incentivized

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.

Incentivized

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.

Incentivized

Essentially, for a question of reliability and scalability, the performance has always been of an enterprise level. The utilities are efficient and effective.

Incentivized

I've only worked with products that do one thing before, but there's so much that Cache offers versus piecing different services together manually. Not only does the product offer a more robust tool-set, but the support is wonderful and I've never encountered a better vendor in any industry in terms of how well they interact with their customers and care about helping you solve your problems. They want you to grow and to get better.

Incentivized

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.

• The investment made about 20 years ago that has been fully repaid
• Reliability and security of investments
• Unfortunately, it is quite outdated and therefore maintenance costs are higher because the skills are not always available.

Incentivized

• Implementation time could be speeded up
• It is very flexible and attractive

Incentivized

• 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