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CouchDB vs Percona: What are the differences?
# Introduction
1. **Scalability**: CouchDB is designed to scale horizontally by distributing data across multiple servers, while Percona offers scalability through clustering and sharding techniques.
2. **Data Modeling**: CouchDB employs a flexible schema-less data model using JSON documents, whereas Percona utilizes a traditional relational database model with defined table structures.
3. **Query Language**: CouchDB uses MapReduce functions for querying data, which can be complex for some users, whereas Percona employs SQL for querying, which is more familiar to many developers.
4. **Replication**: CouchDB has built-in multi-master replication, enabling data replication between multiple nodes in real-time, while Percona's replication is typically master-slave based.
5. **Consistency**: CouchDB offers eventual consistency, meaning changes will eventually propagate across the system, while Percona ensures immediate consistency through strict transactions.
6. **Administration**: CouchDB has a web-based administrative interface for managing and monitoring the database, while Percona provides command-line tools and monitoring solutions for administration.
In Summary, the key differences between CouchDB and Percona lie in their approach to scalability, data modeling, query language, replication, consistency, and administration. Each has distinct features that cater to different use cases and preferences.
Decisions about CouchDB and Percona
Gabriel Pa
CEO at NaoLogic Inc · | 10 upvotes · 454K views
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.
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Learn MorePros of CouchDB
Pros of Percona
Pros of CouchDB
- JSON43
- Open source30
- Highly available18
- Partition tolerant12
- Eventual consistency11
- Sync7
- REST API5
- Attachments mechanism to docs4
- Multi master replication4
- Changes feed3
- REST interface1
- js- and erlang-views1
Pros of Percona
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What is CouchDB?
Apache CouchDB is a database that uses JSON for documents, JavaScript for MapReduce indexes, and regular HTTP for its API. CouchDB is a database that completely embraces the web. Store your data with JSON documents. Access your documents and query your indexes with your web browser, via HTTP. Index, combine, and transform your documents with JavaScript.
What is Percona?
It delivers enterprise-class software, support, consulting and managed services for both MySQL and MongoDB across traditional and cloud-based platforms.
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What are some alternatives to CouchDB and Percona?
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Couchbase
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
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.
MariaDB
Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.
RethinkDB
RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.