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.
N/A
SingleStore
Score 8.2 out of 10
N/A
SingleStore aims to enable organizations to scale from one to one million customers, handling SQL, JSON, full text and vector workloads in one unified platform.
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.
Good for Applications needing instant insights on large, streaming datasets. Applications processing continuous data streams with low latency. When a multi-cloud, high-availability database is required When NOT to Use Small-scale applications with limited budgets Projects that do not require real-time analytics or distributed scaling Teams without experience in distributed databases and HTAP architectures.
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.
It does not release a patch to have back porting; it just releases a new version and stops support; it's difficult to keep up to that pace.
Support engineers lack expertise, but they seem to be improving organically.
Lacks enterprise CDC capability: Change data capture (CDC) is a process that tracks and records changes made to data in a database and then delivers those changes to other systems in real time.
For enterprise-level backup & restore capability, we had to implement our model via Velero snapshot backup.
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.
[Until it is] supported on AWS ECS containers, I will reserve a higher rating for SingleStore. Right now it works well on EC2 and serves our current purpose, [but] would look forward to seeing SingleStore respond to our urge of feature in a shorter time period with high quality and security.
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.
SingleStore excels in real-time analytics and low-latency transactions, making it ideal for operational analytics and mixed workloads. Snowflake shines in batch analytics and data warehousing with strong scalability for large datasets. SingleStore offers faster data ingestion and query execution for real-time use cases, while Snowflake is better for complex analytical queries on historical data.
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.
The support deep dives into our most complexed queries and bizarre issues that sometimes only we get comparing to other clients. Our special workload (thousands of Kafka pipelines + high concurrency of queries). The response match to the priority of the request, P1 gets immediate return call. Missing features are treated, they become a client request and being added to the roadmap after internal consideration on all client needs and priority. Bugs are patched quite fast, depends on the impact and feasible temporary workarounds. There is no issue that we haven't got a proper answer, resolution or reasoning
We allowed 2-3 months for a thorough evaluation. We saw pretty quickly that we were likely to pick SingleStore, so we ported some of our stored procedures to SingleStore in order to take a deeper look. Two SingleStore people worked closely with us to ensure that we did not have any blocking problems. It all went remarkably smoothly.
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.
Greenplum is good in handling very large amount of data. Concurrency in Greenplum was a major problem. Features available in SingleStore like Pipelines and in memory features are not available in Greenplum. Gemfire was not scaling well like SingleStore. Support of both Greenplum and Gemfire was not good. Product team did not help us much like the ones in SingleStore who helped us getting started on our first cluster very fast.
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
As the overall performance and functionality were expanded, we are able to deliver our data much faster than before, which increases the demand for data.
Metadata is available in the platform by default, like metadata on the pipelines. Also, the information schema has lots of metadata, making it easy to load our assets to the data catalog.
