DBMS > Cubrid vs. HBase vs. YDB

System Properties Comparison Cubrid vs. HBase vs. YDB

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Editorial information provided by DB-Engines

Name

Description

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Wide column store

Document store
Relational DBMS

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

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Score	0.34
Rank	#285	Overall
	#43	Document stores
	#130	Relational DBMS

Website

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

hbase.apache.org

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

cubrid.org/manuals

hbase.apache.org/book.html

ydb.tech/en/docs

Developer

CUBRID Corporation, CUBRID Foundation

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Yandex

Initial release

2008

2019

Current release

11.0, January 2021

2.3.4, January 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache version 2

Open Source

Apache 2.0; commercial license available

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++, Java

Java

Server operating systems

Linux
Windows

Linux
Unix
Windows

using Cygwin

Linux

Data scheme

yes

schema-free, schema definition possible

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

yes

SQL-like query language (YQL)

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Java API
RESTful HTTP API
Thrift

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

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

C
C#
C++
Groovy
Java
PHP
Python
Scala

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Access rights defined for Yandex Cloud users

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