DBMS > GBase vs. HBase vs. JaguarDB vs. Oracle NoSQL

System Properties Comparison GBase vs. HBase vs. JaguarDB vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

Performant, highly scalable DBMS for AI and IoT applications

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Relational DBMS

Wide column store

Key-value store
Vector DBMS

Document store
Key-value store
Relational DBMS

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

www.gbase.cn

hbase.apache.org

www.jaguardb.com

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

hbase.apache.org/book.html

www.jaguardb.com/support.html

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

General Data Technology Co., Ltd.

Apache Software Foundation

Apache top-level project, originally developed by Powerset

DataJaguar, Inc.

Oracle

Initial release

2004

2008

2015

2011

Current release

GBase 8a, GBase 8s, GBase 8c

2.3.4, January 2021

3.3 July 2023

23.3, December 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

GPL V3.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, Java, Python

Java

C++

the server part. Clients available in other languages

Java

Server operating systems

Linux

Linux
Unix
Windows

using Cygwin

Linux

Linux
Solaris SPARC/x86

Data scheme

yes

schema-free, schema definition possible

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

optional

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

Standard with numerous extensions

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like DML and DDL statements

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

Java API
RESTful HTTP API
Thrift

JDBC
ODBC

RESTful HTTP API

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Multi-source replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

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)

configurable

ACID within a storage node (=shard)

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

off heap cache

User concepts

Access control

yes

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

rights management via user accounts

Access rights for users and roles

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