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.
Cost Effective & Flexible: Customers can start as low as a single OCPU VM up to 24 OCPUs. Customers pay only for OCPUs and Storage used.
Ease Of Getting Started: Customers can easily create Oracle Certified, full-featured, fully supported 11g, 12c (both 12.1 & 12.2) databases with choice of any database edition.
Built-in High Availability Constructs: Customers can easily deploy 2-node RAC configurations with all the VM shapes. For example: Easily deploy a 2-node RAC configuration with 2 core Virtual Machines and shared block storage of up to 40 TB.
Durable & Scalable Storage: Customers can use remote storage starting at 256GB up to 40 TB. Storage can be scale up with no downtime.
Secure: Customers still get all the advantages of our Oracle IAM for management control and VCN Security lists for securing their database environments.
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.
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.
When we restart the DBaaS instance, it seems like we had to add the NIC network back again. I'm not sure if it's specific to our instance configuration!
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
I would prefer the oracle database as service where my complete implementation is on Oracle Cloud Platform and as BI Implementation where datawarehouse is built on oracle database.
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.
Billing on Hosted Environment per hour, OCPU per hour, block volumes, object storage, etc.
Costing & maintenance, patching.
Security & TDE cycles.
Backups & recovery.
The features are complemented by database lifecycle management features, like configuration management, performance management, patch automation, etc. which make the solution complete from a DBaaS administrator’s perspective as well.
Manager 12c covers all the major use cases for DBaaS, which yield significant business benefits and high ROI.
