DBMS > Cubrid vs. Firebase Realtime Database vs. GeoMesa vs. Riak KV vs. Riak TS

System Properties Comparison Cubrid vs. Firebase Realtime Database vs. GeoMesa vs. Riak KV vs. Riak TS

Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Distributed, fault tolerant key-value store

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Time Series DBMS

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

cubrid.com (korean)
cubrid.org (english)

firebase.google.com/products/realtime-database

www.geomesa.org

Technical documentation

cubrid.org/manuals

firebase.google.com/docs/database

www.geomesa.org/documentation/stable/user/index.html

www.tiot.jp/riak-docs/riak/kv/latest

www.tiot.jp/riak-docs/riak/ts/latest

Developer

CUBRID Corporation, CUBRID Foundation

Google

acquired by Google 2014

CCRi and others

OpenSource, formerly Basho Technologies

Open Source, formerly Basho Technologies

Initial release

2008

2012

2014

2009

2015

Current release

11.0, January 2021

4.0.5, February 2024

3.2.0, December 2022

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache License 2.0

Open Source

Apache version 2, commercial enterprise edition

Open Source

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++, Java

Scala

Erlang

Server operating systems

Linux
Windows

hosted

Linux
OS X

Data scheme

yes

schema-free

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

restricted

SQL

Support of SQL

yes

yes, limited

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Android
iOS
JavaScript API
RESTful HTTP API

HTTP API
Native Erlang Interface

Supported programming languages

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Java
JavaScript
Objective-C

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Java Stored Procedures

limited functionality with using 'rules'

Erlang

Triggers

yes

Callbacks are triggered when data changes

yes

pre-commit hooks and post-commit hooks

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

depending on storage layer

selectable replication factor

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

if the client is offline
Immediate Consistency

if the client is online

depending on storage layer

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

links between datasets can be stored

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

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.

depending on storage layer

User concepts

Access control

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

yes

depending on the DBMS used for storage

yes, using Riak Security

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More resources

DB-Engines blog posts

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