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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. CouchDB vs InfluxDB

CouchDB vs InfluxDB

OverviewDecisionsComparisonAlternatives

Overview

CouchDB
CouchDB
Stacks529
Followers584
Votes139
GitHub Stars6.7K
Forks1.1K
InfluxDB
InfluxDB
Stacks1.0K
Followers1.2K
Votes175

CouchDB vs InfluxDB: What are the differences?

Key Differences between CouchDB and InfluxDB

CouchDB and InfluxDB are both popular database management systems, but they have several key differences that set them apart. Here are six specific differences between the two:

  1. Data Model: CouchDB is a document-oriented database that stores data in flexible JSON-like documents, while InfluxDB is a time series database designed for handling high volumes of time-stamped data points, making it ideal for monitoring and analytics.

  2. Query Language: CouchDB uses a JavaScript-based query language called MapReduce for querying and creating views, providing flexibility but potentially requiring more complex coding. In contrast, InfluxDB uses its own query language called InfluxQL, which is specifically optimized for time series data and provides simpler syntax for querying time-based data.

  3. Scalability and Replication: CouchDB supports multi-master replication, allowing multiple copies of the database to be synchronized and updated independently. This provides high availability and scalability but may introduce conflicts that need to be resolved. InfluxDB, on the other hand, has built-in clustering and highly available distributed architectures, making it more scalable for handling large volumes of time series data.

  4. Data Retention: InfluxDB has built-in support for data retention policies, which allow automatic deletion of old data based on predefined criteria such as time duration. This feature helps manage storage requirements for time series data. In contrast, CouchDB does not have built-in data retention policies, requiring manual data management and potential scalability challenges with large datasets.

  5. Write Performance: InfluxDB is optimized for fast writes and can handle high write loads, making it suitable for real-time data ingestion. CouchDB, on the other hand, may have slower write performance, particularly in scenarios with heavy write operations or concurrent updates.

  6. Community and Ecosystem: CouchDB has a larger and more mature community with a wider range of available libraries, frameworks, and tools. It is also supported by Couchbase, a company providing enterprise service and support. InfluxDB has a smaller but rapidly growing community with a specific focus on time series data, and it is backed by InfluxData, the company behind InfluxDB.

In summary, CouchDB is a highly flexible document-oriented database with multi-master replication capabilities, while InfluxDB is a specialized time series database optimized for handling high volumes of time-stamped data with efficient storage and querying capabilities.

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Advice on CouchDB, InfluxDB

Gabriel
Gabriel

CEO at Naologic

Jan 2, 2020

DecidedonCouchDBCouchDBCouchbaseCouchbaseMemcachedMemcached

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
Deepak
Deepak

Sep 6, 2021

Needs adviceonJSONJSONInfluxDBInfluxDB

Hi all, I am trying to decide on a database for time-series data. The data could be tracking some simple series like statistics over time or could be a nested JSON (multi-level nested). I have been experimenting with InfluxDB for the former case of a simple list of variables over time. The continuous queries are powerful too. But for the latter case, where InfluxDB requires to flatten out a nested JSON before saving it into the database the complexity arises. The nested JSON could be objects or a list of objects and objects under objects in which a complete flattening doesn't leave the data in a state for the queries I'm thinking.

[ 
  { "timestamp": "2021-09-06T12:51:00Z",
    "name": "Name1",
    "books": [
        { "title": "Book1", "page": 100 },
        { "title": "Book2", "page": 280 },
    ]
  },
 { "timestamp": "2021-09-06T12:52:00Z",
   "name": "Name2",
   "books": [
       { "title": "Book1", "page": 320},
       { "title": "Book2", "page": 530 },
       { "title": "Book3", "page": 150 },
   ]
 }
]

Sample query: With a time range, for name xyz, find all the book title for which # of page < 400.

If I flatten it completely, it will result in fields like books_0_title, books_0_page, books_1_title, books_1_page, ... And by losing the nested context it will be hard to return one field (title) where some condition for another field (page) satisfies.

Appreciate any suggestions. Even a piece of generic advice on handling the time-series and choosing the database is welcome!

30.5k views30.5k
Comments
Anonymous
Anonymous

Apr 21, 2020

Needs advice

We are building an IOT service with heavy write throughput and fewer reads (we need downsampling records). We prefer to have good reliability when comes to data and prefer to have data retention based on policies.

So, we are looking for what is the best underlying DB for ingesting a lot of data and do queries easily

381k views381k
Comments

Detailed Comparison

CouchDB
CouchDB
InfluxDB
InfluxDB

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.

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

Terrific single-node database; Clustered database ; HTTP/JSON; Offline first data sync
Time-Centric Functions;Scalable Metrics; Events;Native HTTP API;Powerful Query Language;Built-in Explorer
Statistics
GitHub Stars
6.7K
GitHub Stars
-
GitHub Forks
1.1K
GitHub Forks
-
Stacks
529
Stacks
1.0K
Followers
584
Followers
1.2K
Votes
139
Votes
175
Pros & Cons
Pros
  • 43
    JSON
  • 30
    Open source
  • 18
    Highly available
  • 12
    Partition tolerant
  • 11
    Eventual consistency
Pros
  • 59
    Time-series data analysis
  • 30
    Easy setup, no dependencies
  • 24
    Fast, scalable & open source
  • 21
    Open source
  • 20
    Real-time analytics
Cons
  • 4
    Instability
  • 1
    HA or Clustering is only in paid version
  • 1
    Proprietary query language

What are some alternatives to CouchDB, InfluxDB?

MongoDB

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

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

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

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

SQLite

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

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

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

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

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

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.

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