CouchDB vs UnQLite

Overview

CouchDB

Stacks529

Followers584

Votes139

GitHub Stars6.7K

Forks1.1K

UnQLite

Stacks6

Followers51

Votes0

GitHub Stars2.3K

Forks174

CouchDB vs UnQLite: What are the differences?

# Introduction
In this comparison, we will explore the key differences between CouchDB and UnQLite, two popular NoSQL databases.

1. **Data Model**: CouchDB is a document-oriented database that stores data in JSON format and supports nested data structures, offering flexibility and ease of use. On the other hand, UnQLite is a key-value store that stores data in a simple key-value format, making it efficient for fast data retrieval but less flexible compared to CouchDB.

2. **Query Language**: CouchDB uses MapReduce functions for querying data, allowing complex queries to be performed efficiently. In contrast, UnQLite supports a simple key-value lookup mechanism, which is suitable for straightforward queries but may be limited in handling complex queries that require aggregation and manipulation.

3. **Consistency Model**: CouchDB provides eventual consistency by default, allowing for faster performance and scalability in distributed environments. In contrast, UnQLite offers strong consistency, ensuring that all replicas have the most up-to-date data at all times, but this may impact performance in large-scale deployments.

4. **Replication**: CouchDB has built-in support for peer-to-peer replication, making it easy to synchronize data between different instances and devices. UnQLite, on the other hand, lacks built-in replication features, requiring developers to implement custom replication mechanisms if needed, which can be more complex and error-prone.

5. **Storage Engine**: CouchDB uses an append-only B-tree storage engine, which provides efficient storage and retrieval of data, especially for large data sets. In comparison, UnQLite uses a hybrid storage engine that combines B-tree and log-structured storage, offering a balance between read and write performance but may not be as optimized for specific use cases.

6. **Programming Language Support**: CouchDB supports a wide range of programming languages through its HTTP API, allowing developers to interact with the database using their preferred language. In contrast, UnQLite has native bindings for C/C++, making it suitable for integration with applications written in those languages but may lack support for other popular programming languages.

In Summary, the key differences between CouchDB and UnQLite lie in their data model, query language, consistency model, replication, storage engine, and programming language support, influencing their suitability for different use cases and environments.

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Advice on CouchDB, UnQLite

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	UnQLite
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.	UnQLite is a in-process software library which implements a self-contained, serverless, zero-configuration, transactional NoSQL database engine. UnQLite is a document store database similar to MongoDB, Redis, CouchDB etc. as well a standard Key/Value store similar to BerkeleyDB, LevelDB, etc.
Terrific single-node database; Clustered database ; HTTP/JSON; Offline first data sync	-
Statistics
GitHub Stars 6.7K	GitHub Stars 2.3K
GitHub Forks 1.1K	GitHub Forks 174
Stacks 529	Stacks 6
Followers 584	Followers 51
Votes 139	Votes 0
Pros & Cons
Pros 43 JSON 30 Open source 18 Highly available 12 Partition tolerant 11 Eventual consistency	Cons 1 Different compilation for each platform

What are some alternatives to CouchDB, UnQLite?

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 UnQLite: What are the differences?

# Introduction
In this comparison, we will explore the key differences between CouchDB and UnQLite, two popular NoSQL databases.

1. **Data Model**: CouchDB is a document-oriented database that stores data in JSON format and supports nested data structures, offering flexibility and ease of use. On the other hand, UnQLite is a key-value store that stores data in a simple key-value format, making it efficient for fast data retrieval but less flexible compared to CouchDB.

2. **Query Language**: CouchDB uses MapReduce functions for querying data, allowing complex queries to be performed efficiently. In contrast, UnQLite supports a simple key-value lookup mechanism, which is suitable for straightforward queries but may be limited in handling complex queries that require aggregation and manipulation.

3. **Consistency Model**: CouchDB provides eventual consistency by default, allowing for faster performance and scalability in distributed environments. In contrast, UnQLite offers strong consistency, ensuring that all replicas have the most up-to-date data at all times, but this may impact performance in large-scale deployments.

4. **Replication**: CouchDB has built-in support for peer-to-peer replication, making it easy to synchronize data between different instances and devices. UnQLite, on the other hand, lacks built-in replication features, requiring developers to implement custom replication mechanisms if needed, which can be more complex and error-prone.

5. **Storage Engine**: CouchDB uses an append-only B-tree storage engine, which provides efficient storage and retrieval of data, especially for large data sets. In comparison, UnQLite uses a hybrid storage engine that combines B-tree and log-structured storage, offering a balance between read and write performance but may not be as optimized for specific use cases.

6. **Programming Language Support**: CouchDB supports a wide range of programming languages through its HTTP API, allowing developers to interact with the database using their preferred language. In contrast, UnQLite has native bindings for C/C++, making it suitable for integration with applications written in those languages but may lack support for other popular programming languages.

CouchDB vs UnQLite

Overview