DBMS > Apache Drill vs. Cubrid vs. GridDB vs. Microsoft Azure Table Storage vs. mSQL

System Properties Comparison Apache Drill vs. Cubrid vs. GridDB vs. Microsoft Azure Table Storage vs. mSQL

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

Scalable in-memory time series database optimized for IoT and Big Data

A Wide Column Store for rapid development using massive semi-structured datasets

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Document store
Relational DBMS

Secondary database models

Key-value store
Relational DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Website

drill.apache.org

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

griddb.net

azure.microsoft.com/en-us/services/storage/tables

hughestech.com.au/products/msql

Technical documentation

drill.apache.org/docs

cubrid.org/manuals

docs.griddb.net

Developer

Apache Software Foundation

CUBRID Corporation, CUBRID Foundation

Toshiba Corporation

Microsoft

Hughes Technologies

Initial release

2012

2008

2013

2012

1994

Current release

1.20.3, January 2023

11.0, January 2021

5.1, August 2022

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

free licenses can be provided

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux

hosted

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

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

SQL SELECT statement is SQL:2003 compliant

yes

SQL92, SQL-like TQL (Toshiba Query Language)

A subset of ANSI SQL is implemented

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

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

RESTful HTTP API

JDBC
ODBC

Supported programming languages

C++

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

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

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

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID at container level

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

Access rights based on private key authentication or shared access signatures

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

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