Couchbase Server

Couchbase is being used across our entire organization as the primary database for our platform. It addresses the need for sub-millisecond db transactions at hundreds of thousands of high-availability transactions per second[.]

• Massive concurrency enabling an enormous scale for our platform
• Super-fast transactions enabling a real-time experience across multiple clients

Amazon DynamoDB, MongoDB, Amazon Elasticsearch Service and Elasticsearch

Amazon Managed Streaming for Apache Kafka (Amazon MSK), Amazon Aurora, Amazon CloudFront, Amazon Elastic Container Service (Amazon ECS), Amazon DynamoDB

We are using Couchbase for web application development. Our main focus is public safety and disaster management. We have web and mobile platform presence. We had to solve the syncing issue between mobile and web and Couchbase sync gateway was a great help in this scenario. Also, creating custom document id was another big help for filtering data. Using SDK we perform micro data manipulation processes which is faster comparatively.

• We did not have to use any other solution for synchronisations
• We did not have to use different db/service for elastic search
• Recommended cluster configuration is expensive for small companies or start-ups

MongoDB and PostgreSQL

MongoDB, MySQL, Microsoft Teams

Couchbase is used by teams in our organization to store and manage customer data. Couchbase allows huge scalability and performance which is why it is the database of choice for many teams within our organization. Couchbase is also very easy to configure and deploy to various teams. This allows my team, to just be on stand-by for any upgrades.

• ROI
• Reduced TOIL
• Easy migration

MongoDB and Apache Cassandra

MongoDB, Docker, GitHub

Couchbase connects us to reliable network sources that can effectively manage our data. It is highly scalable and ensures that all data from our customers is effectively managed for better planning. It provides cloud services that customize all data and saves the most useful data that transform our company.

• The performance has enhanced positive Returns on Investment.
• It has been able to control and manage all our databases.

Couchbase was originally selected to be the OLTP database to be used with "the experience engine" to hold the guest information, messaging, activity records, tags/classifications and related information pertaining to the guest experience. We initially used Couchbase prior to the creation of N1QL, and have used its core data services, views (now deprecated), N1QL, and XDCR and SyncGateway functionality. (Our use of couch-base included multi-instance replication). More recently, we've also worked with its event functionality and transactional support (a relatively new addition to its SDK).

• There have been several areas of our application [that] really needed an ACID compliant database (e.g. strong transactional guarantees) that we thought we could work around while using Couchbase. [In my opinion] that turned out to be a poor bet. You need to be certain that the specific characteristics of a NoSQL database fit your problem.
• Couchbase does eliminate the need for schema upgrades completely. I.e no downtime or conversion windows as you migrate your data model, adding attributes, etc. This helped with the deployment timeframe associated with DB changes.
• The database is (apparently) a bit more of a space/memory consumer than originally anticipated. During deployments, we received constant pressure from Couchbase consulting teams to eliminate/reduce the number of indexes, and this was because any mutations to docs in a bucket must check for impact against all indexes. More recent years have started to address this with their "collections" features, which helps isolate indexes to specific sub-groupings of documents.

Oracle Java SE, Kubernetes, PostgreSQL