Likelihood to Recommend 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 I find HDP easy to use and solves most of the problems for people looking to manage their big data. Evaluating the Hortonworks Data Platform is easy as it is free to download and install in your cluster. Single node cluster available as Sandbox is also easy for POCs.
Read full review Pros 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 It does a good job of packaging a lot of big data components into bundles and lets you use the ones you are interested in or need. It supports an extensive list of components which lets us solve many problems. It provides the ability to manage installations and maintenance using Apache Ambari. It helps us in using management packs to install/upgrade components easily. It also helps us add, remove components, add, remove hosts, perform upgrades in a convenient manner. It also provides alerts and notifications and monitors the environment. What they excel in is packaging open source components that are relevant and are useful to solve and complement each other as well as contribute to enhancing those components. They do a great job in the community to keep on top of what would be useful to users, fixing bugs and working with other companies and individuals to make the platform better. Read full review Cons 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 Since it doesn't come with propriety tools for big data management, additional integration is need (for query handling, search, etc). It was very straightforward to store clinical data without relations, such as data from sensors of a medical device. But it has limitations when needed to combine the data with other clinical data in structured format (e.g. lab results, diagnosis). Overall look and feel of front-end management tools (e.g. monitoring) are not good. It is not bad but it doesn't look professional. Read full review Likelihood to Renew 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 It’s great tool but it can be complicated when it comes administration and maintenance.
Read full review Support Rating Sometimes instead giving straight answer, we ‘re getting transfered to talk professional service.
Read full review Implementation Rating Try not to change variable names.
Read full review Alternatives Considered 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 We chose [Hortonworks Data Platform] because it's free and because [it] was an IBM partner, suggested as big data platform after biginsights platform.
You can install in more physical computer without high specs, then you can use it in order to learn how to deploy, configure a complete big data cluster.
We installed also in a cloud infrastructure of 5 virtual machine
Read full review Return on Investment 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 It is difficult to have a negative impact, because the required investment is not that high. The big open community behind Hortonworks and related Apache Project makes it easy to put 'the wheel to meet the road' quite quickly. We have seen management meetings where the attendants were impressed by the results achieved with the datalake built on HDP. Read full review ScreenShots