Couchbase Server is a cloud-native, distributed database that fuses the strengths of relational databases such as SQL and ACID transactions with JSON flexibility and scale that defines NoSQL. It is available as a service in commercial clouds and supports hybrid and private cloud deployments.
Against HBase, writes were faster. Reads not so much. Also ability to store in other formats would be good (such as objects). Compared to aerospike, does not compare. Aerospike blows it out of water.
It was packaged with the vendor product we bought. Also, it’s good for high performance transactional systems. I'm part of our NoSQL team and Cassandra quickly became a favorite for developers with agile teams.
Cassandra does one thing very well. It's able to collect any type of metrics and analytics and store them at very fast speeds. But when it comes to reading the data, there are minor performance issues. That's when other databases such as couchdb or couchbase come in. They can …
The Apache Cassandra was one type of product used in our company for a couple of use-cases. The Aerospike is something we [analyzed] not so long time ago as an interesting alternative, due to its performance characteristics. The Oracle Coherence was and is still being used for …
Easy to deploy and manage. Clustering and replication is fairly simple and straightforward. According to developers, Couchbase scored higher points compared to the other products that we evaluated.
Couchbase had more features than the other products we evaluated and a more flexible data model. It also has global replication and better performance. Compared to some, it was also easier to deploy, manage, and scale. The global replication, plus the ease of deploying and …
We looked at several different SQL and NoSQL systems. Most were either too expensive, didn't provide the needed functionality, or were too hard to use with the size of our team. We ultimately went with Couchbase because of its performance, horizontal scalability, and price.
We selected CB as it provided the highest performance DB we evaluated while still providing a relatively rich set of additional features at competitive pricing.
We selected Couchbase because it was recommended internally. We've had more success with Cassandra in the past, and with its simpler, more intuitive data model. Full text search makes us sometimes favour Couchbase though.
Scalable architecture, data first concept, cross data center replication support, running indexing as a separate service, JSON document makes easy readable format. Also, Couchbase’s integration with Kubernates really opens up a lot of possibilities when it comes down to a …
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.
Best suited when edge devices have interrupted internet connection. And Couchbase provides reliable data transfer. If used for attachment Couchbase has a very poor offering. A hard limit of 20 MB is not okay. They have the best conflict resolution but not so great query language on Couchbase lite.
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.
The N1QL engine performs poorly compared to SQL engines due to the number of interactions needed, so if your use case involves the need for a lot of SQL-like query activity as opposed to the direct fetch of data in the form of a key/value map you may want to consider a RDBMS that has support for json data types so that you can more easily mix the use of relational and non-relational approaches to data access.
You have to be careful when using multiple capabilities (e.g. transactions with Sync Gateway) as you will typically run into problems where one technology may not operate correctly in combination with another.
There are quality problems with some newly released features, so be careful with being an early adopter unless you really need the capability. We somewhat desperately adopted the use of transactions, but went through multiple bughunt cycles with Couchbase working the kinks out.
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.
I rarely actually use Couchbase Server, I just stay up-to-date with the features that it provides. However, when the need arises for a NoSQL datastore, then I will strongly consider it as an option
Couchbase has been quite a usable for our implementation. We had similar experience with our previous "trial" implementation, however it was short lived.
Couchbase has so far exceeded expectation. Our implementation team is more confident than ever before.
When we are Live for more than 6 months, I'm hoping to enhance this rating.
One of Couchbase’s greatest assets is its performance with large datasets. Properly set up with well-sized clusters, it is also highly reliable and scalable. User management could be better though, and security often feels like an afterthought. Couchbase has improved tremendously since we started using it, so I am sure that these issues will be ironed out.
I haven't had many opportunities to request support, I will look forward to better the rating. We have technical development and integration team who reach out directly to TAM at Couchbase.
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 Apache Cassandra was one type of product used in our company for a couple of use-cases. The Aerospike is something we [analyzed] not so long time ago as an interesting alternative, due to its performance characteristics. The Oracle Coherence was and is still being used for [the] distributed caching use-case, but it will be replaced eventually by Couchbase. Though each of these products [has] its own strengths and weaknesses, we prefer sticking to Couchbase because of [the] experience we have with this product and because it is cost-effective for our organization.
So far, the way that we mange and upgrade our clusters has be very smooth. It works like a dream when we use it in concert with AWS and their EC2 machines. Having access to powerful instances along side the Couchbase interface is amazing and allows us to do rebalances or maintenance without a worry
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.
