CouchDB vs KairosDB

Overview

CouchDB

Stacks529

Followers584

Votes139

GitHub Stars6.7K

Forks1.1K

KairosDB

Stacks16

Followers44

Votes5

GitHub Stars1.8K

Forks345

CouchDB vs KairosDB: What are the differences?

Key Differences between CouchDB and KairosDB

Data Model: CouchDB is a document-oriented database that stores data in a schema-free JSON format, allowing for flexibility and easy handling of diverse data structures. In contrast, KairosDB is a time-series database specifically designed for storing timestamped data points, making it ideal for monitoring and analytics applications.
Query Language: CouchDB uses MapReduce functions or Mango Query Language (based on MongoDB's query language) for data retrieval and manipulation. On the other hand, KairosDB provides a RESTful API for querying time-series data through a variety of functions and filters optimized for time-based operations.
Scaling Capabilities: CouchDB offers horizontal scaling through its built-in clustering mechanism, allowing for high availability and fault tolerance. In comparison, KairosDB relies on external solutions like Apache Cassandra or HBase for distributed storage and scalability, providing flexibility but requiring additional setup and maintenance.
Use Cases: CouchDB is well-suited for applications that require flexible data models, offline support, and peer-to-peer synchronization, such as mobile apps or content management systems. Meanwhile, KairosDB excels in scenarios that involve large volumes of timestamped data, like IoT sensor data analysis, log monitoring, or metric tracking in DevOps environments.
Community and Ecosystem: CouchDB has a mature and active community with extensive documentation, tools, and support resources available for developers. In contrast, KairosDB, being a more specialized solution, may have a smaller user base and fewer third-party integrations and plugins.
Ease of Setup and Maintenance: CouchDB is known for its ease of installation, setup, and administration, with features like automatic compaction and conflict resolution simplifying database management tasks. On the other hand, KairosDB may require more configuration and monitoring due to its dependence on external databases for storage and scalability management.

In Summary, the key differences between CouchDB and KairosDB lie in their data models, query languages, scaling capabilities, use cases, community support, and ease of setup and maintenance.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs

CLI (Node.js)

Manual

Advice on CouchDB, KairosDB

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.

592k views592k

Comments

Detailed Comparison

CouchDB	KairosDB
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.	KairosDB is a fast distributed scalable time series database written on top of Cassandra.
Terrific single-node database; Clustered database ; HTTP/JSON; Offline first data sync	-
Statistics
GitHub Stars 6.7K	GitHub Stars 1.8K
GitHub Forks 1.1K	GitHub Forks 345
Stacks 529	Stacks 16
Followers 584	Followers 44
Votes 139	Votes 5
Pros & Cons
Pros 43 JSON 30 Open source 18 Highly available 12 Partition tolerant 11 Eventual consistency	Pros 1 Open source 1 As fast as your cassandra/scylla cluster go 1 Time-Series data analysis 1 Easy setup 1 Easy Rest API

What are some alternatives to CouchDB, KairosDB?

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 KairosDB: What are the differences?

Key Differences between CouchDB and KairosDB

Data Model: CouchDB is a document-oriented database that stores data in a schema-free JSON format, allowing for flexibility and easy handling of diverse data structures. In contrast, KairosDB is a time-series database specifically designed for storing timestamped data points, making it ideal for monitoring and analytics applications.
Query Language: CouchDB uses MapReduce functions or Mango Query Language (based on MongoDB's query language) for data retrieval and manipulation. On the other hand, KairosDB provides a RESTful API for querying time-series data through a variety of functions and filters optimized for time-based operations.
Scaling Capabilities: CouchDB offers horizontal scaling through its built-in clustering mechanism, allowing for high availability and fault tolerance. In comparison, KairosDB relies on external solutions like Apache Cassandra or HBase for distributed storage and scalability, providing flexibility but requiring additional setup and maintenance.
Use Cases: CouchDB is well-suited for applications that require flexible data models, offline support, and peer-to-peer synchronization, such as mobile apps or content management systems. Meanwhile, KairosDB excels in scenarios that involve large volumes of timestamped data, like IoT sensor data analysis, log monitoring, or metric tracking in DevOps environments.
Community and Ecosystem: CouchDB has a mature and active community with extensive documentation, tools, and support resources available for developers. In contrast, KairosDB, being a more specialized solution, may have a smaller user base and fewer third-party integrations and plugins.
Ease of Setup and Maintenance: CouchDB is known for its ease of installation, setup, and administration, with features like automatic compaction and conflict resolution simplifying database management tasks. On the other hand, KairosDB may require more configuration and monitoring due to its dependence on external databases for storage and scalability management.

In Summary, the key differences between CouchDB and KairosDB lie in their data models, query languages, scaling capabilities, use cases, community support, and ease of setup and maintenance.

CouchDB vs KairosDB

Overview