Apache Cassandra is a NoSQL database and well suited where you need highly available, linearly scalable, tunable consistency and high performance across varying workloads. It has worked well for our use cases, and I shared my experiences to use it effectively at the last Cassandra summit! http://bit.ly/1Ok56TK It is a NoSQL database, finally you can tune it to be strongly consistent and successfully use it as such. However those are not usual patterns, as you negotiate on latency. It works well if you require that. If your use case needs strongly consistent environments with semantics of a relational database or if the use case needs a data warehouse, or if you need NoSQL with ACID transactions, Apache Cassandra may not be the optimum choice.
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.
Continuous availability: as a fully distributed database (no master nodes), we can update nodes with rolling restarts and accommodate minor outages without impacting our customer services.
Linear scalability: for every unit of compute that you add, you get an equivalent unit of capacity. The same application can scale from a single developer's laptop to a web-scale service with billions of rows in a table.
Amazing performance: if you design your data model correctly, bearing in mind the queries you need to answer, you can get answers in milliseconds.
Time-series data: Cassandra excels at recording, processing, and retrieving time-series data. It's a simple matter to version everything and simply record what happens, rather than going back and editing things. Then, you can compute things from the recorded history.
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.
Cassandra runs on the JVM and therefor may require a lot of GC tuning for read/write intensive applications.
Requires manual periodic maintenance - for example it is recommended to run a cleanup on a regular basis.
There are a lot of knobs and buttons to configure the system. For many cases the default configuration will be sufficient, but if its not - you will need significant ramp up on the inner workings of Cassandra in order to effectively tune it.
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.
I would recommend Cassandra DB to those who know their use case very well, as well as know how they are going to store and retrieve data. If you need a guarantee in data storage and retrieval, and a DB that can be linearly grown by adding nodes across availability zones and regions, then this is the database you should choose.
We evaluated MongoDB also, but don't like the single point failure possibility. The HBase coupled us too tightly to the Hadoop world while we prefer more technical flexibility. Also HBase is designed for "cold"/old historical data lake use cases and is not typically used for web and mobile applications due to its performance concern. Cassandra, by contrast, offers the availability and performance necessary for developing highly available applications. Furthermore, the Hadoop technology stack is typically deployed in a single location, while in the big international enterprise context, we demand the feasibility for deployment across countries and continents, hence finally we are favor of Cassandra
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.
I have no experience with this but from the blogs and news what I believe is that in businesses where there is high demand for scalability, Cassandra is a good choice to go for.
Since it works on CQL, it is quite familiar with SQL in understanding therefore it does not prevent a new employee to start in learning and having the Cassandra experience at an industrial level.
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
