DBMS > Cubrid vs. IBM Db2 warehouse vs. Snowflake vs. Splice Machine vs. TerminusDB

System Properties Comparison Cubrid vs. IBM Db2 warehouse vs. Snowflake vs. Splice Machine 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

Cloud-based data warehousing service

Cloud-based data warehousing service for structured and semi-structured data

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

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

Primary database model

Relational DBMS

Graph DBMS

Secondary database models

Document store
RDF store

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Trend Chart

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

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

www.ibm.com/products/db2/warehouse

www.snowflake.com

splicemachine.com

terminusdb.com

Technical documentation

cubrid.org/manuals

docs.snowflake.net/manuals/index.html

splicemachine.com/how-it-works

terminusdb.github.io/terminusdb/#

Developer

CUBRID Corporation, CUBRID Foundation

IBM

Snowflake Computing Inc.

Splice Machine

DataChemist Ltd.

Initial release

2008

2014

2018

Current release

11.0, January 2021

3.1, March 2021

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

AGPL 3.0, commercial license available

Open Source

GPL V3

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

Prolog, Rust

Server operating systems

Linux
Windows

hosted

Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (WOQL)

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

.NET Client API
JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript (Node.js)
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

JavaScript
Python

Server-side scripts

Stored procedures

Java Stored Procedures

PL/SQL, SQL PL

user defined functions

yes

Java

yes

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Shared Nothhing Auto-Sharding, Columnar Partitioning

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication
Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights for users, groups and roles according to SQL-standard

Role-based access control

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