CouchDB vs OrientDB

Overview

CouchDB

Stacks529

Followers584

Votes139

GitHub Stars6.7K

Forks1.1K

OrientDB

Stacks77

Followers107

Votes14

CouchDB vs OrientDB: What are the differences?

Introduction

CouchDB and OrientDB are two popular NoSQL databases with different features and functionalities. In this comparison, we will highlight the key differences between CouchDB and OrientDB.

Data Model: CouchDB is a document-oriented database that stores data in JSON documents, making it easy to work with semi-structured data. OrientDB, on the other hand, is a multi-model database that supports document, key-value, graph, and object-oriented models. It offers flexibility in choosing the most appropriate data model for various use cases.
Scalability: CouchDB is designed to be a horizontally scalable database, meaning it can handle large amounts of data by distributing it across multiple servers. It uses a master-less architecture that enables easy replication and synchronization. OrientDB, on the other hand, is known for its multi-threaded, multi-master architecture, which makes it highly scalable and suitable for handling real-time transactions and concurrent writes.
Query Language: CouchDB uses JavaScript-based MapReduce functions for querying and aggregating data. This allows for complex queries and data transformations. On the other hand, OrientDB supports SQL-like query language (called OrientSQL) and also provides a built-in graph query language called Gremlin. This makes it easier for developers familiar with SQL to work with the database.
ACID Compliance: CouchDB is designed to provide eventual consistency, which means that updates are asynchronous and data may not immediately be consistent across all replicas. It offers a form of strong consistency through its use of conflict resolution algorithms when conflicts occur. OrientDB, on the other hand, supports ACID (Atomicity, Consistency, Isolation, Durability) transactions, providing strong consistency and reliability for critical data.
Concurrency Control: CouchDB uses optimistic concurrency control, where conflicts can occur when multiple clients update the same document simultaneously. It provides conflict detection and resolution mechanisms to handle such conflicts. OrientDB, on the other hand, supports optimistic and pessimistic concurrency control. It allows for explicit locking of resources to prevent conflicts and ensures data consistency.
Graph Database Capabilities: OrientDB has built-in support for graph databases, allowing for efficient traversal and querying of connected data. It provides features like automatic relationship discovery and indexing for graph-oriented operations. CouchDB, on the other hand, does not have direct support for graph databases and may require additional data modeling and indexing techniques to handle graph-like structures efficiently.

In summary, CouchDB is a document-oriented database with horizontal scalability and eventual consistency, while OrientDB is a multi-model database with support for various data models, ACID compliance, and powerful querying capabilities. The decision between the two would depend on the specific requirements of the application and the preferred data model.

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Advice on CouchDB, OrientDB

Gabriel

CEO at Naologic

Jan 2, 2020

Decidedon

CouchDB

Couchbase

Memcached

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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Comments

Detailed Comparison

CouchDB	OrientDB
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.	It is an open source NoSQL database management system written in Java. It is a Multi-model database, supporting graph, document, key/value, and object models, but the relationships are managed as in graph databases with direct connections between records.
Terrific single-node database; Clustered database ; HTTP/JSON; Offline first data sync	-
Statistics
GitHub Stars 6.7K	GitHub Stars -
GitHub Forks 1.1K	GitHub Forks -
Stacks 529	Stacks 77
Followers 584	Followers 107
Votes 139	Votes 14
Pros & Cons
Pros 43 JSON 30 Open source 18 Highly available 12 Partition tolerant 11 Eventual consistency	Pros 4 Great graphdb 2 Open source 2 Great support 1 Performance 1 Rest api Cons 4 Unstable

What are some alternatives to CouchDB, OrientDB?

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.

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

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.

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

Related Comparisons

CouchDB vs OrientDB: What are the differences?

Introduction

CouchDB and OrientDB are two popular NoSQL databases with different features and functionalities. In this comparison, we will highlight the key differences between CouchDB and OrientDB.

Data Model: CouchDB is a document-oriented database that stores data in JSON documents, making it easy to work with semi-structured data. OrientDB, on the other hand, is a multi-model database that supports document, key-value, graph, and object-oriented models. It offers flexibility in choosing the most appropriate data model for various use cases.
Scalability: CouchDB is designed to be a horizontally scalable database, meaning it can handle large amounts of data by distributing it across multiple servers. It uses a master-less architecture that enables easy replication and synchronization. OrientDB, on the other hand, is known for its multi-threaded, multi-master architecture, which makes it highly scalable and suitable for handling real-time transactions and concurrent writes.
Query Language: CouchDB uses JavaScript-based MapReduce functions for querying and aggregating data. This allows for complex queries and data transformations. On the other hand, OrientDB supports SQL-like query language (called OrientSQL) and also provides a built-in graph query language called Gremlin. This makes it easier for developers familiar with SQL to work with the database.
ACID Compliance: CouchDB is designed to provide eventual consistency, which means that updates are asynchronous and data may not immediately be consistent across all replicas. It offers a form of strong consistency through its use of conflict resolution algorithms when conflicts occur. OrientDB, on the other hand, supports ACID (Atomicity, Consistency, Isolation, Durability) transactions, providing strong consistency and reliability for critical data.
Concurrency Control: CouchDB uses optimistic concurrency control, where conflicts can occur when multiple clients update the same document simultaneously. It provides conflict detection and resolution mechanisms to handle such conflicts. OrientDB, on the other hand, supports optimistic and pessimistic concurrency control. It allows for explicit locking of resources to prevent conflicts and ensures data consistency.
Graph Database Capabilities: OrientDB has built-in support for graph databases, allowing for efficient traversal and querying of connected data. It provides features like automatic relationship discovery and indexing for graph-oriented operations. CouchDB, on the other hand, does not have direct support for graph databases and may require additional data modeling and indexing techniques to handle graph-like structures efficiently.

CouchDB vs OrientDB

Overview

CouchDB vs OrientDB: What are the differences?