DBMS > Cubrid vs. Dgraph vs. Google Cloud Bigtable vs. HyperSQL vs. VoltDB

System Properties Comparison Cubrid vs. Dgraph vs. Google Cloud Bigtable vs. HyperSQL vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

Distributed and scalable native Graph DBMS

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Graph DBMS

Key-value store
Wide column store

Relational DBMS

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

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

dgraph.io

cloud.google.com/bigtable

hsqldb.org

www.voltdb.com

Technical documentation

cubrid.org/manuals

dgraph.io/docs

cloud.google.com/bigtable/docs

hsqldb.org/web/hsqlDocsFrame.html

docs.voltdb.com

Developer

CUBRID Corporation, CUBRID Foundation

Dgraph Labs, Inc.

Google

VoltDB Inc.

Initial release

2008

2016

2015

2001

2010

Current release

11.0, January 2021

2.7.2, June 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Open Source

based on BSD license

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java

Java, C++

Server operating systems

Linux
Windows

Linux
OS X
Windows

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
OS X

for development

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.

Secondary indexes

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP API

JDBC via HTTP
JDBC
ODBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

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

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

All languages supporting JDBC/ODBC
Java

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

Java, SQL

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Synchronous replication via Raft

Internal replication in Colossus, and regional replication between two clusters in different zones

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Atomic single-row operations

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

Planned for future releases

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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