DBMS > Cachelot.io vs. Cubrid vs. HEAVY.AI vs. Tibero

System Properties Comparison Cachelot.io vs. Cubrid vs. HEAVY.AI vs. Tibero

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Editorial information provided by DB-Engines

Name

Description

In-memory caching system

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.00
Rank	#396	Overall
	#64	Key-value stores

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	1.81
Rank	#143	Overall
	#65	Relational DBMS

Website

cachelot.io

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

github.com/heavyai/heavydb
www.heavy.ai

us.tmaxsoft.com/products/tibero

Technical documentation

cubrid.org/manuals

docs.heavy.ai

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

CUBRID Corporation, CUBRID Foundation

HEAVY.AI, Inc.

TmaxSoft

Initial release

2015

2008

2016

2003

Current release

11.0, January 2021

5.10, January 2022

6, April 2015

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

Apache Version 2.0

Open Source

Apache Version 2; enterprise edition available

commercial

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

C++

C, C++, Java

C++ and CUDA

C and Assembler

Server operating systems

FreeBSD
Linux
OS X

Linux
Windows

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Memcached protocol

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

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

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

Java Stored Procedures

Persistent Stored Procedure (PSM)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

In-memory capabilities

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

yes

planned for next version

User concepts

Access control

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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