DBMS > Apache Drill vs. Blueflood vs. Cubrid vs. mSQL vs. Snowflake

System Properties Comparison Apache Drill vs. Blueflood vs. Cubrid vs. mSQL vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

Scalable TimeSeries DBMS based on Cassandra

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

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

Primary database model

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	2.28
Rank	#119	Overall
	#23	Document stores
	#56	Relational DBMS

Score	0.09
Rank	#353	Overall
	#33	Time Series DBMS

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	1.67
Rank	#151	Overall
	#70	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

drill.apache.org

blueflood.io

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

hughestech.com.au/products/msql

www.snowflake.com

Technical documentation

drill.apache.org/docs

github.com/rax-maas/blueflood/wiki

cubrid.org/manuals

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Rackspace

CUBRID Corporation, CUBRID Foundation

Hughes Technologies

Snowflake Computing Inc.

Initial release

2012

2013

2008

1994

2014

Current release

1.20.3, January 2023

11.0, January 2021

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

free licenses can be provided

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

Java

C, C++, Java

Server operating systems

Linux
OS X
Windows

Linux
OS X

Linux
Windows

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

hosted

Data scheme

schema-free

predefined scheme

yes

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

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

A subset of ANSI SQL is implemented

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

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP REST

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

C++

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

C
C++
Delphi
Java
Perl
PHP
Tcl

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

none

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

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

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.