CouchDB VS Memcached

CouchDB

CouchDB is a json based database for simple projects. The fork pouchdb offers lots of support for offline.

Apache CouchDB belongs to the family of NoSQL databases. It is a document store with a strong focus on replication and reliability. One of the most significant differences between CouchDB and a relational database (besides the absence of tables and schemas) is how you query data. Relational databases allow their users to execute arbitrary and dynamic queries via SQL. Each SQL query may look completely different than the previous one. These dynamic aspects are significant for use cases where you work exploratively with your dataset but don't matter as much in a web context. Additionally, defining an index for a specific table is optional. Most developers will define indices to boost performance, but the database does not require it.

I just turns out you can't always do that in a real codebase. For example see here:

  https://github.com/apache/couchdb/blob/23efd8e5b1aa96ef01640fec03a5fedc945ba8b9/src/couch_mrview/src/couch_mrview_http.erl#L228

Example: Apache Cassandra, CouchDB.

For non-SQL-based databases, consider MongoDB, or CouchDB, which are very easy to get started with.

The Apache CouchDB server. It stores Annotation data.

CouchDB

Memcached

> Multiple clients racing can't be fixed.

Really? You can't think of a single way for multiple clients to operate on the same data without racing? (Here's a hint if you're still having trouble: https://github.com/memcached/memcached/wiki/Commands#cas.)

Memcached: A simple, open-source, distributed memory object caching system primarily used for caching strings. Best suited for lightweight, non-persistent caching needs.

Oh, thank you! I didn't realize that LRU Maintainer Thread was more than an expiration reaper. When it was first being introduced that was its first responsibility as lazy expiration removal by size eviction meant dead entries wasted capacity. It was all work in progress when I had read about it [1] and talked to dormando, so it got fuzzy. The compat code [2, 3] might have also thrown me off if I only looked at the setting and not the usage. Its a neat variant to all of these ideas.

[1] https://github.com/memcached/memcached/pull/97

stores session state in a session store like Memcached or Redis.

memcached has recently gained the ability to spill to disk: https://github.com/memcached/memcached/wiki/Extstore

we recently implemented this to grow our caches to >50TB

Django supports using Memcached as a cache backend. Memcached is a high-performance, distributed memory caching system that can be used to store cached data across multiple servers.