One honest answer to this question is easy: CouchDB is an Apache-backed, open source, schema-free database. Helpful? It acknowledges an open secret I’ll blurt out: answering this question is notoriously difficult, because you need to make some assumptions about who you’re answering it for. The other open secret is self-flattery, but as an open source and not marketing-driven technology, we tend to be pretty good here.

Before entertaining the title question, let’s answer your next one: Who is this article for?

If you’re not sure what features it has, who uses CouchDB and when to consider it, you’re part of our audience. Maybe you’ve (intentionally or not) come across it in a comparison table when starting something new, but we’ll assume you haven’t created your own CouchDB instance before.

This article will introduce CouchDB via the technical problems it was first created to address, and cover the headline features. In the next two parts of this series, we’ll look at real-world use cases, guidelines that foster CouchDB’s development, and cover the CouchDB ecosystem.

Don’t want to wait? You can get started with CouchDB in less than 5 minutes (no fluff). Plus, there’s the CouchDB Blog and Documentation.

History of CouchDB and NoSQL

If you were a developer coming up when NoSQL was a buzzword, you will definitely have heard of CouchDB. If not, chances are it came up in your coding course, and you may even have joined the CouchDB Slack to get some help with an assignment.

Having been active for 18+ years, CouchDB’s staying power, more than its origin story, is what makes it interesting. That’s also a testament to the simplicity and stability of it, but we’ll cover CouchDB’s guiding principles in more detail later in the series (if this were a video, here’s where I’d remind you to subscribe so you don’t miss that).

To tell this story, you’ll need to cast your mind back to the days of MySpace Tim, probably around the time you’d be seeing and hearing the last CRT monitors and dial-up tones in friend’s homes and reading about the first iPhone. It’s a time that conjures breakthroughs amidst patchy connections, scarce storage space, and expensive hardware. You may not have experienced these limitations yourself, but they very much informed why CouchDB emerged.

The Problems “NoSQL” Aims to Solve

CouchDB was the first “NoSQL” database to become widely known, so let’s start with why an alternative was necessary, i.e., let’s look at what CouchDB isn’t. By the way, we’re not going to go into the debate over the term “NoSQL” or the history of the wider tech hypecycle. In a world without a globally spanning internet, planning for connectivity failure was (and remains) essential. While SQL databases can manage such conditions, they are by and large designed to expect a stable connection. So how do they handle interruptions? Very broadly, for illustrative purposes:

• SQL databases use transactions to ensure data consistency. In a connectivity failure, incomplete transactions are rolled back to avoid incomplete changes.
• The database may lock the record being written to to avoid conflicts, and wait for a timeout to release it.
• Many SQL databases have a failover mechanism that, if configured, allows a replica server to take over.

Expecting a reliable environment means that recovering from connection problems is possible, but requires careful handling to mitigate likely data loss or corruption.

Because it was slightly before its time, I’ll use an analogy to showcase how things could have looked. If you used Microsoft Word in the very early 2000’s, you’ll be familiar with the novel paperclip assistant who helped with various tasks and suggestions. In the days of manual, local saves, Clippy would hop in after a lost connection or crash and ask “Do you want to recover your document?” You could click your way through to a “recovered” version of your choosing, but you would almost definitely lose work. Maybe a couple of lines, maybe most of the document.

In a world where Clippy runs on CouchDB, you’d get: “It looks like you went offline. Don’t worry! Your document is still here and will sync momentarily.” Tada!

Here we see CouchDB’s fundamental guiding principles in action: Keep user data safe. Regardless of the connection state. To hint at how much better this gets, it’s probably useful to point out here that “Couch” is a backronym for “cluster of unreliable commodity hardware”. CouchDB expects things to fail, not just the network!

CouchDB’s Features

If you haven’t already visited, the CouchDB landing page will greet you with the words:

Seamless multi-primary sync, that scales from big data to mobile, with an intuitive HTTP/JSON API and designed for reliability.

These features make the hero section for a reason, so let’s go through them.

Seamless multi-primary sync

CouchDB makes it reeeally easy to move data around and keep it in sync. How is that useful? Well:

If you need to reset a database to a clean state — whether in development, testing, or production — it’s super easy. Just set up a seed DB, and whenever you need a fresh start, delete the existing one and run a one-time replication.

Want to keep multiple environments in sync? No problem:

• Need a copy of your dev database to revisit later? Just replicate it.
• Want to seed a staging database? Just replicate from a known source.
• Prod broke and you want to reproduce the bug locally with the exact same data? Replicate prod to a local dev environment.
• Running analytics on real-world data and watching your expenses skyrocket? Spin up a separate copy and crunch away.
• Need a live backup but don’t have a dedicated ops team? Continuous replication has you covered.
• Want periodic snapshots as an extra safety net? Run a one-time replication whenever you need.
• Want to run your database across two continents for fault tolerance, like one UPS competitor does, replication is here for you.

Starting a replication is one request. Or a few clicks in Fauxton. Even if you’re not building a distributed system, CouchDB’s replication makes managing data smooth and effortless.

Scales from Big Data to Mobile

CouchDB has been getting the job done for 18+ years and handles huge datasets with ease. Whether you’re running a single instance, a 100-node cluster, or syncing mobile apps, you have to build your app only once and it’ll grow while CouchDB scales up.

Your project might start small, but if it takes off, you don’t have to rewrite it. Just keep using CouchDB the same way. Relax™.

Intuitive HTTP/JSON API

Practically everything in CouchDB has a URL — even restarting the database. Every piece of data, every config setting, every function — accessible over HTTP. And all data is JSON.

That means:

• Works with any tech stack.
• No libraries to research, install, or maintain.
• If you know HTTP and JSON, you already know how to use CouchDB.

CouchDB was the first database to go all-in on JSON. Now, everyone else is playing catch-up.

Designed for Reliability

CouchDB is stubbornly resilient. Other databases can get grumpy if you don’t shut them down just right — sometimes even refusing to start back up until you fix them. CouchDB doesn’t care. Shut down your machine mid-write, pull the plug, crash your system — when it comes back up, CouchDB just picks up where it left off. No corruption, no repairs, no “unclean shutdown” warnings.

Power outage? No problem.

Hardware failure? No problem.

Unexpected crash? No problem.

Start back up and your data is ready to use.

Most databases are delicate once you peek behind the curtain, or worse, have to recover them. I’ve had colleagues get corrupted data just because their laptop went to sleep. Other folks have week-long outages while their database recovery tooling does its job. CouchDB? It just keeps going.

Whatever you’re building — big or small, cloud or mobile, mission-critical or just-for-fun — CouchDB has your back.

All processes in a CouchDB, even the long-running ones like replications, are resumable and can be interrupted as rudely and abruptly as you like. They’ll just continue where they left off. It’ll be fine. If you haven’t already: Relax™.

What’s Next

In part 2, we’ll look at when and why to consider CouchDB and go over some use cases, pulling real-world examples to understand what it’s capable of. Part 3 will focus on the CouchDB ecosystem and community. See you there!

Have you used CouchDB before? Let us know in the comments!

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This article includes some fragments that have been adapted from our blog.