DBMS > Cubrid vs. Google Cloud Spanner vs. RDF4J vs. SQLite vs. SQream DB

System Properties Comparison Cubrid vs. Google Cloud Spanner vs. RDF4J vs. SQLite vs. SQream DB

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 horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Widely used embeddable, in-process RDBMS

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS

RDF store

Relational DBMS

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

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

cloud.google.com/spanner

rdf4j.org

www.sqlite.org

sqream.com

Technical documentation

cubrid.org/manuals

cloud.google.com/spanner/docs

rdf4j.org/documentation

www.sqlite.org/docs.html

docs.sqream.com

Developer

CUBRID Corporation, CUBRID Foundation

Google

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Dwayne Richard Hipp

SQream Technologies

Initial release

2008

2017

2004

2000

2017

Current release

11.0, January 2021

3.46.0 (23 May 2024), May 2024

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Public Domain

commercial

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

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux
Windows

hosted

Linux
OS X
Unix
Windows

server-less

Linux

Data scheme

yes

RDF Schemas

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

yes, ANSI Standard SQL Types

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

Query statements complying to ANSI 2011

yes

SQL-92 is not fully supported

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

.Net
JDBC
ODBC

Supported programming languages

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

Go
Java
JavaScript (Node.js)
Python

Java
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication with 3 replicas for regional instances.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

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

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

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