RavenDB is a NoSQL Document Database that is fully transactional (ACID) across the database and throughout clusters. It is presented as an easy to use all-in-one database that minimizes the need for third party addons, tools, or support to boost developer productivity and get projects into production fast. Users can setup and secure a data cluster deploy in the cloud, on…
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Apache Cassandra
RavenDB
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Cassandra
RavenDB
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Apache Cassandra
RavenDB
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Cassandra
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RavenDB
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Chose RavenDB
The given alternatives are also powerful and really good noSQL databases but the highest availability of RavenDB allows me/us to know it a lot better. RavenDB is encrypted by default wherever we use it in production and it has a high level of documents compression.
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.
If you're a.NET developer searching for a system other than SQL Server for business assessment, then you must try RavenDB. RavenDB is a fantastic document-oriented system that has been specifically developed to work with all.NET or Windows systems. Developers are continually working on such systems to eliminate their flaws while also providing a few benefits. We must refresh ourselves on a regular basis since the free software system is like an open area where anybody may stand up with a brilliant solution to the issue. RavenDB is absolutely worth a look
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.
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've had an excellent experience using RavenDB. Internally we are testing the newer features in 5.0 such as time series, which will effect the con specified previously dependent on the real world performance. We foresee that BattleCrate will continue to use RavenDB as we grow.
Really good .NET client that is very easy to use. The management studio is excellent and puts anything that Microsoft or Oracle have to shame. Very quick to develop with once the complexity hurdle has been overcome. Initially using it can be a bit painful until you fully grasp the event sourced nature of the indexing.
The support is really fast and flexible. Since one single working day, we got a response to our first request, only 4 days later we got a technical demonstration for our complete developer team to get in touch with raven and its performance. Also during our development, we got a quick response to questions.
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
The given alternatives are also powerful and really good noSQL databases but the highest availability of RavenDB allows me/us to know it a lot better. RavenDB is encrypted by default wherever we use it in production and it has a high level of documents compression.
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.
RavenDB has saved my customers a lot of money with their cloud services' tiered model. The database is able to grow with the project/company and can start out small at a low cost.
RavenDB is free for three nodes and three CPUs, which makes it great for development scenarios. You're able to start rapidly building applications without having to worry about licensing.
Scaling out has allowed us to use three small cloud servers when starting out and get the performance and throughput of a single larger server.