DBMS > Cubrid vs. GeoMesa vs. JanusGraph vs. Riak KV vs. Riak TS

System Properties Comparison Cubrid vs. GeoMesa vs. JanusGraph 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

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph 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)

www.geomesa.org

janusgraph.org

Technical documentation

cubrid.org/manuals

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

docs.janusgraph.org

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

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

Developer

CUBRID Corporation, CUBRID Foundation

CCRi and others

Linux Foundation; originally developed as Titan by Aurelius

OpenSource, formerly Basho Technologies

Open Source, formerly Basho Technologies

Initial release

2008

2014

2017

2009

2015

Current release

11.0, January 2021

4.0.5, February 2024

0.6.3, February 2023

3.2.0, December 2022

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

Scala

Java

Erlang

Server operating systems

Linux
Windows

Linux
OS X
Unix
Windows

Linux
OS X

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

restricted

SQL

Support of SQL

yes

yes, limited

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP API
Native Erlang Interface

Supported programming languages

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

Clojure
Java
Python

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

yes

Erlang

Triggers

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

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

depending on storage layer

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

depending on the DBMS used for storage

User authentification and security via Rexster Graph Server

yes, using Riak Security

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More resources

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