DBMS > Apache IoTDB vs. Couchbase vs. KairosDB vs. OpenQM vs. Sphinx

System Properties Comparison Apache IoTDB vs. Couchbase vs. KairosDB vs. OpenQM vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Distributed Time Series DBMS based on Cassandra or H2

QpenQM is a high-performance, self-tuning, multi-value DBMS

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

iotdb.apache.org

www.couchbase.com

github.com/kairosdb/kairosdb

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

sphinxsearch.com

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

docs.couchbase.com

kairosdb.github.io

sphinxsearch.com/docs

Developer

Apache Software Foundation

Couchbase, Inc.

Rocket Software, originally Martin Phillips

Sphinx Technologies Inc.

Initial release

2018

2011

2013

1993

2001

Current release

1.1.0, April 2023

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

1.2.2, November 2018

3.4-12

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

Open Source

GPL version 2, commercial licence available

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

Java

C, C++, Go and Erlang

Java

C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

with some exceptions

yes

Typing

predefined data types such as float or date

yes

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.

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
Native API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

Graphite protocol
HTTP REST
Telnet API

Proprietary protocol

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java
JavaScript

Node.js
PHP
Python

.Net
Basic
C
Java
Objective C
PHP
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Automatic Sharding

Sharding

based on Cassandra

yes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Multi-source replication

including cross data center replication
Source-replica replication

selectable replication factor

based on Cassandra

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

yes

Ephemeral buckets

User concepts

Access control

yes

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

simple password-based access control

Access rights can be defined down to the item level

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