DBMS > CouchDB vs. HEAVY.AI vs. InfluxDB vs. RocksDB

System Properties Comparison CouchDB vs. HEAVY.AI vs. InfluxDB vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

DBMS for storing time series, events and metrics

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

Spatial DBMS

with GEO package

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

couchdb.apache.org

github.com/heavyai/heavydb
www.heavy.ai

www.influxdata.com/products/influxdb-overview

rocksdb.org

Technical documentation

docs.couchdb.org/en/stable

docs.heavy.ai

docs.influxdata.com/influxdb

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

HEAVY.AI, Inc.

Facebook, Inc.

Initial release

2005

2016

2013

Current release

3.3.3, December 2023

5.10, January 2022

2.7.6, April 2024

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2; enterprise edition available

Open Source

MIT-License; commercial enterprise version available

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Erlang

C++ and CUDA

C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X

through Homebrew

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

via views

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

HTTP API
JSON over UDP

C++ API
Java API

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

All languages supporting JDBC/ODBC/Thrift
Python

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

Round robin

Sharding

in enterprise version only

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

selectable replication factor

in enterprise version only

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

atomic operations within a single document possible

yes

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Depending on used storage engine

yes

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

simple rights management via user accounts

More information provided by the system vendor

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Key customers

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Market metrics

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Licensing and pricing models

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