DBMS > atoti vs. Cubrid vs. Drizzle vs. Hive

System Properties Comparison atoti vs. Cubrid vs. Drizzle vs. Hive

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Primary database model

Object oriented DBMS

Relational DBMS

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Website

atoti.io

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

hive.apache.org

Technical documentation

docs.atoti.io

cubrid.org/manuals

cwiki.apache.org/confluence/display/Hive/Home

Developer

ActiveViam

CUBRID Corporation, CUBRID Foundation

Drizzle project, originally started by Brian Aker

Apache Software Foundation

initially developed by Facebook

Initial release

2008

2012

Current release

11.0, January 2021

7.2.4, September 2012

3.1.3, April 2022

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache Version 2.0

Open Source

GNU GPL

Open Source

Apache Version 2

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

C++

Java

Server operating systems

Linux
Windows

FreeBSD
Linux
OS X

All OS with a Java VM

Data 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.

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

with proprietary extensions

SQL-like DML and DDL statements

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JDBC

JDBC
ODBC
Thrift

Supported programming languages

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

C
C++
Java
PHP

C++
Java
PHP
Python

Server-side scripts

Stored procedures

Python

Java Stored Procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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, multi-version concurrency control (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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users, groups and roles

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