DBMS > Cubrid vs. HEAVY.AI vs. Oracle Berkeley DB vs. Riak KV vs. TerminusDB

System Properties Comparison Cubrid vs. HEAVY.AI vs. Oracle Berkeley DB vs. Riak KV vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

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

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

Widely used in-process key-value store

Distributed, fault tolerant key-value store

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

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

Graph DBMS

Secondary database models

Spatial DBMS

Document store
RDF store

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

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	2.52
Rank	#114	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	4.44
Rank	#80	Overall
	#9	Key-value stores

Score	0.22
Rank	#323	Overall
	#28	Graph DBMS

Website

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

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

www.oracle.com/database/technologies/related/berkeleydb.html

terminusdb.com

Technical documentation

cubrid.org/manuals

docs.heavy.ai

docs.oracle.com/cd/E17076_05/html/index.html

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

terminusdb.github.io/terminusdb/#

Developer

CUBRID Corporation, CUBRID Foundation

HEAVY.AI, Inc.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

OpenSource, formerly Basho Technologies

DataChemist Ltd.

Initial release

2008

2016

1994

2009

2018

Current release

11.0, January 2021

5.10, January 2022

18.1.40, May 2020

3.2.0, December 2022

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

commercial license available

Open Source

Apache version 2, commercial enterprise edition

Open Source

GPL V3

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

C, C++, Java

C++ and CUDA

C, Java, C++ (depending on the Berkeley DB edition)

Erlang

Prolog, Rust

Server operating systems

Linux
Windows

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X

Linux

Data scheme

yes

schema-free

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

only with the Berkeley DB XML edition

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

SQL-like query language (WOQL)

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC
Thrift
Vega

HTTP API
Native Erlang Interface

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

All languages supporting JDBC/ODBC/Thrift
Python

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

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

JavaScript
Python

Server-side scripts

Stored procedures

Java Stored Procedures

Erlang

yes

Triggers

yes

only for the SQL API

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

none

Sharding

no "single point of failure"

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

Source-replica replication

selectable replication factor

Journaling Streams

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

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

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

in-memory journaling

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes, using Riak Security

Role-based access control

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