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Cloudant vs Couchbase: What are the differences?
Developers describe Cloudant as "Distributed database-as-a-service (DBaaS) for web & mobile apps". Cloudant’s distributed database as a service (DBaaS) allows developers of fast-growing web and mobile apps to focus on building and improving their products, instead of worrying about scaling and managing databases on their own. On the other hand, Couchbase is detailed as "Document-Oriented NoSQL Database". Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.
Cloudant can be classified as a tool in the "NoSQL Database as a Service" category, while Couchbase is grouped under "Databases".
Some of the features offered by Cloudant are:
- Managed- Cloudant's big data experts monitor your data 24/7 to ensure its high availability and safety.
- Distributed Multi-Master Database- All read and write transactions can be synced across Cloudant's global data network without global locks, providing true high availability of your data.
- Geo-load Balancing- To keep latency low, our geo-load balancing infrastructure routes requests to the copies of the data that are geographically closest to the requestor.
On the other hand, Couchbase provides the following key features:
- JSON document database
- N1QL (SQL-like query language)
- Secondary Indexing
"JSON" is the primary reason why developers consider Cloudant over the competitors, whereas "Flexible data model, easy scalability, extremely fast" was stated as the key factor in picking Couchbase.
We Have thousands of .pdf docs generated from the same form but with lots of variability. We need to extract data from open text and more important - from tables inside the docs. The output of Couchbase/Mongo will be one row per document for backend processing. ADOBE renders the tables in an unusable form.
I prefer MongoDB due to own experience with migration of old archive of pdf and meta-data to a new “archive”. The biggest advantage is speed of filters output - a new archive is way faster and reliable then the old one - but also the the easy programming of MongoDB with many code snippets and examples available. I have no personal experience so far with Couchbase. From the architecture point of view both options are OK - go for the one you like.
I would like to suggest MongoDB or ArangoDB (can't choose both, so ArangoDB). MongoDB is more mature, but ArangoDB is more interesting if you will need to bring graph database ideas to solution. For example if some data or some documents are interlinked, then probably ArangoDB is a best solution.
To process tables we used Abbyy software stack. It's great on table extraction.
If you can select text with mouse drag in PDF. Use pdftotext it is fast! You can install it on server with command "apt-get install poppler-utils". Use it like "pdftotext -layout /path-to-your-file". In same folder it will make text file with line by line content. There is few classes on git stacks that you can use, also.
We implemented our first large scale EPR application from naologic.com using CouchDB .
Very fast, replication works great, doesn't consume much RAM, queries are blazing fast but we found a problem: the queries were very hard to write, it took a long time to figure out the API, we had to go and write our own @nodejs library to make it work properly.
It lost most of its support. Since then, we migrated to Couchbase and the learning curve was steep but all worth it. Memcached indexing out of the box, full text search works great.
Pros of Cloudant
- JSON13
- REST interface7
- Cheap4
- JavaScript support3
- Great syncing1
Pros of Couchbase
- High performance18
- Flexible data model, easy scalability, extremely fast18
- Mobile app support9
- You can query it with Ansi-92 SQL7
- All nodes can be read/write6
- Equal nodes in cluster, allowing fast, flexible changes5
- Both a key-value store and document (JSON) db5
- Open source, community and enterprise editions5
- Automatic configuration of sharding4
- Local cache capability4
- Easy setup3
- Linearly scalable, useful to large number of tps3
- Easy cluster administration3
- Cross data center replication3
- SDKs in popular programming languages3
- Elasticsearch connector3
- Web based management, query and monitoring panel3
- Map reduce views2
- DBaaS available2
- NoSQL2
- Buckets, Scopes, Collections & Documents1
- FTS + SQL together1
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Cons of Cloudant
Cons of Couchbase
- Terrible query language3
