Getting up to speed with CouchDB

Getting Up to Speed with CouchDB

Last week, as part of a writing gig I was pitching, I dug into CouchDB, a distributed document database management system. While this won’t pass as normal fare for my typical blogging-oriented audience, I was fascinated by the system and want to share it with you.

Ready? Let’s get to it.

Introducing CouchDB

CouchDB is fault-tolerant, scalable, and designed for distributed replication. It was designed from the ground-up as a distributed document database system and is powered by Erlang/OTP to take advantage of the platform’s reliability and concurrent availability. It’s a worthy candidate for all types of distributed document database applications, from mobile apps to big data.

Seamless Distributed Replication

CouchDB is a peer-based document storage system that supports full replication of data and applications across multiple instances. Complete and partial remote database instances can be replicated for offline, remote operation, and document revisions replicated bidirectionally between all instances the next time they are connected.

Documents: A More Natural Data Storage Format

Data stored in CouchDB is organized into documents rather than the tables you might be used to if you deal primarily with relational databases. Documents are schema-free records that neatly encapsulate related data in a way that mirrors real-world documents. CouchDB never overwrites committed data or data structures. Instead, when a document is updated, a serialized revision is appended to the stored document, allowing for all document revisions to be reviewed incrementally.

A Flexible System of Views

The view system consists of designs documents which aggregate and report data. Views are built dynamically on-demand and generate a static snapshot which remains unchanged throughout the viewing session. Underlying documents can change without locking out or interrupting a reader’s view.

Extendable Security

CouchDB ships with a simple and extendable security model to manage reader access and validate updates. Reader access is managed by database admins who update design documents that generate reader views. As data is updated, it is checked dynamically for security and data validation. User credentials can be compared against fields in the existing document to verify ownership prior to writing, or more advanced user permission validation models can be implemented.

CouchDB is Easy

Pick CouchDB and you’ll be working with technologies you already know such as the REST API to read and write data, and JavaScript to write design documents, validate data updates, and create filters.

In addition, with CouchDB concurrency is baked-in. Any number of clients will be able to read and refresh views while the source documents are being updated, all without ever locking out or interrupting a reader.

Finally, CouchDB is designed for failure — power failure that is. When a system crash or power failure happens mid-update, no data will be corrupted thanks to the way CouchDB appends all revisions to the end of the document. When the system reboots, CouchDB will be immediately available, and the partial update will be recommitted in full.

Don’t Get off the CouchDB

CouchDB isn’t the right solution for every data storage question. If your data sets are highly relational, an RDBMS is probably a better option. However, if you want an easy-to-use system to build a distributed document management application that will maintain full revision history, CouchDB is the relaxing choice.

Learn More

The official CouchDB documentation site is excellent and offers a wealth of tutorials and guides to help you get started with CouchDB.

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