TrustRadius Insights for Apache CouchDB are summaries of user sentiment data from TrustRadius reviews and, when necessary, third party data sources.
Business Problems Solved
CouchDB has proven to be a valuable tool in various industries and projects. For instance, it is widely used in the Big Data Insight Product Division for development and production environment setups. Its flexibility and scalability make it an attractive alternative to relational databases like MySQL, especially when handling large amounts of unstructured data. In media-oriented companies such as advertising and film, CouchDB is utilized to manage vast quantities of distributed and rapidly changing file sets.
Additionally, CouchDB finds its utility in mobile applications that require offline data storage. The sync capability of the database has been highly beneficial in ensuring seamless data availability even when users are offline. Legacy applications that previously relied on SQL databases have successfully migrated to CouchDB, resulting in improved response times. Another use case involves route planning for sales forces, where CouchDB serves as a central farm for mobile devices, with content partitioned per user.
Moreover, CouchDB plays a crucial role in storing time-series data for test sensor networks, while introducing users to non-SQL concepts and technologies. Its simplicity, ease of setup and configuration, and developer friendliness have made it the go-to NoSQL database server for globally used network testing and security products. Customers value CouchDB for its ability to save and access thousands of crucial documents representing vital information for their activities.
Furthermore, CouchDB is leveraged by Datawhere, a file intelligence platform that helps individuals and businesses find digital assets across platforms, devices, and geographic barriers. By working seamlessly with Logstash and Elasticsearch, CouchDB provides fast and powerful search functionality for customers. It also assists in storing a million SERP pages gathered daily and parsing them to find ads on each page.
Overall, CouchDB's diverse use cases span from social media analytics systems to file management in media-oriented companies, enabling offline data storage in mobile apps, facilitating database migration from SQL systems, supporting route planning for sales forces, storing time-series data for sensor networks, and serving as the main NoSQL information database server for global network testing and security products. Its versatility, reliability, and ease of use position it as a valuable tool in various domains.
Currently, we use CouchDB in various projects throughout our Big Data Insight Product Division for development and production environment setup. Mainly it is being used to store serialized (JSON formatted) unstructured data. For our development environment, usually, a single node DB is more than sufficient for prototyping and to deliver Minimum Viable Product (MVP). However, for production setup, which demands High Availability (HA), a cluster DB with replication capability is a must.
Pros
Serialized objects can be stored as unstructured data in JSON formatted documents highly desirable for Web and Mobile Applications.
RESTful HTTP API provides flexible and seamless database operations.
Scalable distributed high availability solution with replication capability for redundant data storage.
Cons
NoSQL DB can become a challenge for seasoned RDBMS users.
The map-reduce paradigm can be very demanding for first-time users.
JSON format documents with Key-Value pairs are somewhat verbose and consume more storage.
Likelihood to Recommend
CouchDB is particularly suitable for storing unstructured or semi-structured data that does not require strict fields and data types. JSON document with RESTful HTTP API for operation is highly desirable to be stored as a serialized object for Web and Mobile applications. However, NoSQL and Map-Reduce paradigm might be a significant hurdle to integrate with SQL-RDBMS system.
There are multiple legacy applications which use SQL databases as a backend for services which are invoked from POS systems. We managed to migrate these applications to CouchDB which provided a faster response.
Pros
Faster retrieval is the main key. When the data is denormalized in required format, the response time for queries without id columns are really fast in CouchDB.
Replacing Oracle views to bucket structure provides great readability and flexibility to the data.
Writing multiple views supporting the needs that will perform the action in an equal amount of time makes CouchDB the favourite database for query-like micro services.
Cons
Views need to be more easier for creation.
Documentation is the key for the development with multiple languages which this lacks.
Likelihood to Recommend
Well Suited: Services/applications that return or act as a backend to the application that require a fast throughput. Less Appropriate: Data structure is too complex to do denormalization and will require multiple hops to serve one request.
CouchDB was used for data replication across different audiences and when users were in offline mode (no/low internet). It was initially used as a proof of concept with an intent to use across mobile apps.
Pros
Replication sync
NoSql schema
Small client side implementation (PouchDB)
Cons
Better client side/mobile implemention
Alway room for improvement for documentation
Likelihood to Recommend
I feel as though CouchDB is a real contender in the NoSQL DB space.
VU
Verified User
Manager in Information Technology (Defense & Space company, 10,001+ employees)