DBMS > Blueflood vs. Cubrid vs. Ingres vs. mSQL vs. Spark SQL

System Properties Comparison Blueflood vs. Cubrid vs. Ingres vs. mSQL vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

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

Well established RDBMS

mSQL (Mini SQL) is a simple and lightweight RDBMS

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Time Series DBMS

Relational DBMS

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

blueflood.io

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

www.actian.com/databases/ingres

hughestech.com.au/products/msql

spark.apache.org/sql

Technical documentation

github.com/rax-maas/blueflood/wiki

cubrid.org/manuals

docs.actian.com/ingres

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Rackspace

CUBRID Corporation, CUBRID Foundation

Actian Corporation

Hughes Technologies

Apache Software Foundation

Initial release

2013

2008

1974

originally developed at University Berkely in early 1970s

1994

2014

Current release

11.0, January 2021

11.2, May 2022

4.4, October 2021

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

free licenses can be provided

Open Source

Apache 2.0

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

Java

C, C++, Java

Scala

Server operating systems

Linux
OS X

Linux
Windows

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X
Windows

Data scheme

predefined scheme

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like DML and DDL statements

APIs and other access methods

HTTP REST

ADO.NET
JDBC
ODBC
OLE DB

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

JDBC
ODBC

Supported programming languages

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

C
C++
Delphi
Java
Perl
PHP
Tcl

Java
Python
R
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

horizontal partitioning

Ingres Star to access multiple databases simultaneously

none

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

Ingres Replicator

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

none

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

MVCC

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

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