CouchDB supports master-master setups with automatic conflict detection.
CouchDB comes with a suite of features, such as on-the-fly document transformation and real-time change notifications, that makes web app development a breeze. It even comes with an easy to use web administration console. You guessed it, served up directly out of CouchDB!
We care a lot about distributed scaling. CouchDB is highly available and partition tolerant, but is also eventually consistent. And we care a lot about your data. CouchDB has a fault-tolerant storage engine that puts the safety of your data first.
Erlang, a concurrent, functional programming language with an emphasis on fault tolerance.
Early work on CouchDB was started in C++ but was replaced by Erlang OTP platform. Erlang has so far proven an excellent match for this project.
- The first is a storage limitation of 2 Giga bytes per file.
- The second is that it requires a validation and fix up cycle after a crash or power failure, so even if the size limitation is lifted, the fix up time on large files is prohibitive.
- Mnesia replication is suitable for clustering, but not disconnected, distributed edits. Most of the “cool” features of Mnesia aren’t really useful for CouchDB.
- Also Mnesia isn’t really a general-purpose, large scale database. It works best as a configuration type database, the type where the data isn’t central to the function of the application, but is necessary for the normal operation of it. Think things like network routers, HTTP proxies and LDAP directories, things that need to be updated, configured and reconfigured often, but that configuration data is rarely very large.
CouchDB uses an “Optimistic concurrency” model. In the simplest terms, this just means that you send a document version along with your update, and CouchDB rejects the change if the current document version doesn’t match what you’ve sent.
You can re-frame many normal transaction based scenarios for CouchDB. You do need to sort of throw out your RDBMS domain knowledge when learning CouchDB, though.
It’s helpful to approach problems from a higher level, rather than attempting to mold Couch to a SQL based world.
MongoDB and CouchDB are document oriented database.
MongoDB and CouchDB are the most typical representative of the open source NoSQL database.
They have nothing in common other than are stored in the document outside.
MongoDB and CouchDB, the data model interface, object storage and replication methods have many different.
PouchDB is also a CouchDB client, and you should be able to switch between a local database or an online CouchDB instance without changing any of your application’s code.
However, there are some minor differences to note:
View Collation – CouchDB uses ICU to order keys in a view query; in PouchDB they are ASCII ordered.
View Offset – CouchDB returns an offset property in the view results. In PouchDB, offset just mirrors the skip parameter rather than returning a true offset.
Erlang is a great fit for CouchDB and I have absolutely no plans to move the project off its Erlang base. IBM/Apache’s only concerns are we remove license incompatible 3rd party source code bundled with the project, a fundamental requirement for any Apache project. So some things may have to replaced in the source code (possibly Mozilla Spidermonkey), but the core Erlang code stays.
An important goal is to keep interfaces in CouchDB simple enough that creating compatible implementations on other platforms is feasible. CouchDB has already inspired the database projects RDDB and Basura. Like SQL databases, I think CouchDB needs competition and a ecosystem to be viable long term. So Java or C++ versions might be created and I would be delighted to see them, but it likely won’t be me who does it.
The main consequences of IBM’s involvement are:
– The code is now being Apache licensed, instead of GPL.
– Damien is going to be contributing much more time!
JSON Documents – Everything stored in CouchDB boils down to a JSON document.
RESTful Interface – From creation to replication to data insertion, every management and data task in CouchDB can be done via HTTP.
N-Master Replication – You can make use of an unlimited amount of ‘masters’, making for some very interesting replication topologies.
Built for Offline – CouchDB can replicate to devices (like Android phones) that can go offline and handle data sync for you when the device is back online.
Replication Filters – You can filter precisely the data you wish to replicate to different nodes.
CouchDB allows you to write a client side application that talks directly to the Couch without the need for a server side middle layer, significantly reducing development time. With CouchDB, you can easily handle demand by adding more replication nodes with ease. CouchDB allows you to replicate the database to your client and with filters you could even replicate that specific user’s data.
Having the database stored locally means your client side application can run with almost no latency. CouchDB will handle the replication to the cloud for you. Your users could access their invoices on their mobile phone and make changes with no noticeable latency, all whilst being offline. When a connection is present and usable, CouchDB will automatically replicate those changes to your cloud CouchDB.
CouchDB is a database designed to run on the internet of today for today’s desktop-like applications and the connected devices through which we access the internet.
Couchdbkit’s goal is to provide a framework for your Python application to access and manage Couchdb. It provides you a full featured and easy client to access and manage CouchDB. It allows you to manage a CouchDB server, databases, doc managements and view access. All objects mostly reflect python objects for convenience. Server and Databases objects could be used for example as easy as using a dict.