CouchDB vs Hadoop: What are the differences?
CouchDB and Hadoop can be categorized as "Databases" tools.
"JSON" is the primary reason why developers consider CouchDB over the competitors, whereas "Great ecosystem" was stated as the key factor in picking Hadoop.
CouchDB and Hadoop are both open source tools. Hadoop with 9.18K GitHub stars and 5.74K forks on GitHub appears to be more popular than CouchDB with 4.22K GitHub stars and 833 GitHub forks.
Slack, Shopify, and SendGrid are some of the popular companies that use Hadoop, whereas CouchDB is used by BrightMachine, Third Iron, and SocialDecode. Hadoop has a broader approval, being mentioned in 237 company stacks & 116 developers stacks; compared to CouchDB, which is listed in 60 company stacks and 30 developer stacks.
What is CouchDB?
What is Hadoop?
Want advice about which of these to choose?Ask the StackShare community!
What are the cons of using CouchDB?
What are the cons of using Hadoop?
What tools integrate with CouchDB?
What tools integrate with Hadoop?
The MapReduce workflow starts to process experiment data nightly when data of the previous day is copied over from Kafka. At this time, all the raw log requests are transformed into meaningful experiment results and in-depth analysis. To populate experiment data for the dashboard, we have around 50 jobs running to do all the calculations and transforms of data.
Document (JSON) DB.
- - queries must be pre-defined as views (not as flexible as query formulation on the fly)
- - community and ecosystem not as large as mongodb
- + PouchDB is an excellent JS library to interact with CouchDB or even work in offline-then-sync moce
in 2009 we open sourced mrjob, which allows any engineer to write a MapReduce job without contending for resources. We’re only limited by the amount of machines in an Amazon data center (which is an issue we’ve rarely encountered).
By being built on, of, in and around CouchDB, Smileupps offers to its customers secure and reliable CouchDB hosting and a CouchDB-based app store to build and sell serious business-enabled web applications
The massive volume of discovery data that powers Pinterest and enables people to save Pins, create boards and follow other users, is generated through daily Hadoop jobs...
Importing/Exporting data, interpreting results. Possible integration with SAS
TBD. Good to have I think. Analytics on loads of data, recommendations?