IBM Informix creates an effective and secure channel for easy and quick data management and transfer across other major Cloud platforms and other data storage systems. The analytical ability is also the best and most effective visual functionalities and the encryption and the data archiving functionalities are great and easy on reporting.
MonetDB is great when you are performing adhoc queries on a large set of data. For example, if you store data in a typical RDBMS such as MySQL or Postgres and want to join large tables for analytics but the query runs unacceptably slow then MonetDB can act as a second database to offload complex queries. Based on my experience, it may not be a production-ready database since there aren't many DBAs familiar with it and due to lack of documentation, maintenance can become a little tricky.
Excellent Data Warehouse performance from the basic engine. Outstanding Data Warehouse performance from the Informix Warehouse Accelerator module.
Best embedability among major RDBMS systems.
Scalable from the smallest Raspberry PI up to the largest monolithic systems and out to dozens of distributed nodes.
Hybrid data capabilities to merge relational data with time seriesv, geospacial data, JSON data and other non-traditional data types with performance comparable or better than systems dedicated to those data types.
It is very difficult to find a missing functionality in Informix, technically is great. I will again criticize the business side and how it has been managed over the past, I hope this could be improved with HCL's help. I know they are working hard, but we need to start letting the world know and revert their concept about its existence and that it is one of the best competitors within the data treatment, in the market. We need to start telling the world about success cases and stories showing this and backing up its strong technology.
This is an open source software so there are obvious drawbacks, the biggest of which is a lack of documentation.
MonetDB does not seem to be well known outside of the academic environment so there is less information when you are searching for answers of any type.
I'd like to see more use cases and/or best practices so that commercial companies like ours can optimally use all of its highly performant features.
The code is written in C/C++ and this can be negative if you are a mainly java-shop and need UDF - User Defined Function.
IBM Informix creates effective solutions for big data extraction and data transportation functionalities across the entire Cloud services and the Automation ability is the best. The security that IBM Informix provides for all our business data and other project information and contacts is effective and the reports are very clean and easy to understand.
We have used Five9 in my previous company but on a much smaller scale. It was more expensive, however we were using it for a max of 50 employees, now we need a much bigger platform. We also used Five9 for other things, like phone dialers etc. so it was a little different.
Although I do not own nor have visibility on my company's figures:
Informix generates consistent savings on DBA staffing, no need for many DBAs as other DBMS require.
The replication architecture allowed consistent savings in the infrastructure as well as developments and maintenance, the job is already done, no need to develop complex and costly solutions, it's just a matter of configuring it.
The advantages of hybrid development (i.e mixing SQL and NoSQL in the same database) is not just a marketing hype: it allowed us to solve with a brilliant solution, in one afternoon of coding, a functional problem we have been having for more than 10 years!
The biggest drawback is that IBM pricing may be constraining, it has too important gaps between the mid range and highrange in terms of pricing
If you are familiar with a general database concept and played with open source products before then MonetDB will give you immediate return in terms of productivity since developers can quickly develop and verify their test cases involving back-end database with a large sample data set.
There is a stiff learning curve due to lack of documentation and sparse information available on the internet.
Overall experience has been positive since MonetDB gives you another option when it comes to building out a data warehouse.
