Likelihood to Recommend We were developing an advertisement time auction application, where we had to store the client's personal details, advertisement-related details, location, and many other details. Moreover, we required a promotion, cookies, and a few more details from the front end. All this information is heavy in terms of size and cannot be lost if the server crash. So, we required an extremely fast disk database with high scalability and low throughput.
Read full review 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.
Read full review Pros Low latency Stable Highly configurable increasing features Read full review 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. Read full review Cons Load balancing per network segments. Reduction in price. Cross datacenter replication usage isn't so straightforward. Sometimes cross dc replication can have issues of bad data.. Read full review 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. Read full review Likelihood to Renew If money isn't an issue, and you're not on the cloud, then I'd go with Aerospike. If you're the cloud ie, aws or azure, then i'd stick with dynamoDB or Cosmos then. Aerospike is definitely not something you want to put into the cloud. It doesn't work well w/ cross regions. If cross DC, you'll have to write some stuff for data integrity checks.
Read full review 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.
Read full review Usability We were in dilemma in deciding the database and it was the first time we were using Aerospike. Eventually, everything went as expected and resolved the client's requirement along with positive feedback and appreciation
Read full review It’s great tool but it can be complicated when it comes administration and maintenance.
Read full review Support Rating You pay for the level of support.
Read full review Sometimes instead giving straight answer, we ‘re getting transfered to talk professional service.
Read full review Alternatives Considered Aerospike is much more performant than
MongoDB , however there is much greater community adoption and support for mongo
Read full review 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
Read full review Return on Investment increased response time minimal managerial resource required developer can start using with shallow learning curve Read full review 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. Read full review ScreenShots