DBMS > Altibase vs. Couchbase vs. CouchDB vs. Firebase Realtime Database vs. Hawkular Metrics

System Properties Comparison Altibase vs. Couchbase vs. CouchDB vs. Firebase Realtime Database vs. Hawkular Metrics

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

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

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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Primary database model

Relational DBMS

Document store

Time Series DBMS

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

Spatial DBMS

using the Geocouch extension

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Website

altibase.com

www.couchbase.com

couchdb.apache.org

firebase.google.com/products/realtime-database

www.hawkular.org

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.couchbase.com

docs.couchdb.org/en/stable

firebase.google.com/docs/database

www.hawkular.org/hawkular-metrics/docs/user-guide

Developer

Altibase

Couchbase, Inc.

Apache Software Foundation

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

Google

acquired by Google 2014

Community supported by Red Hat

Initial release

1999

2011

2005

2012

2014

Current release

v7.3, 2023, August 2023

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

3.3.3, December 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

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

Open Source

Apache version 2

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

C, C++, Go and Erlang

Erlang

Java

Server operating systems

AIX
HP-UX
Linux

Linux
OS X
Windows

Android
BSD
Linux
OS X
Solaris
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

yes

via views

yes

SQL

Support of SQL

ANSI SQL-92

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

APIs and other access methods

JDBC
ODBC
Proprietary protocol

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

RESTful HTTP/JSON API

Android
iOS
JavaScript API
RESTful HTTP API

HTTP REST

Supported programming languages

C
C++
Java

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

Java
JavaScript
Objective-C

Go
Java
Python
Ruby

Server-side scripts

Stored procedures

stored procedures and stored functions

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

View functions in JavaScript

limited functionality with using 'rules'

Triggers

yes

via the TAP protocol

yes

Callbacks are triggered when data changes

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

Sharding

improved architecture with release 2.0

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

Ephemeral buckets

User concepts

Access control

fine grained access rights according to SQL-standard

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

Access rights for users can be defined per database

yes, based on authentication and database rules

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