DBMS > jBASE vs. MySQL vs. openGauss vs. PostGIS vs. Vertica

System Properties Comparison jBASE vs. MySQL vs. openGauss vs. PostGIS vs. Vertica

Editorial information provided by DB-Engines

Name

Description

A robust multi-value DBMS comprising development tools and middleware

Widely used open source RDBMS

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

Spatial extension of PostgreSQL

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Multivalue DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Spatial DBMS

Relational DBMS

Column oriented

Secondary database models

Document store
Spatial DBMS

Relational DBMS

Spatial DBMS
Time Series DBMS

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

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.08
Rank	#183	Overall
	#84	Relational DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.mysql.com

gitee.com/opengauss
opengauss.org

postgis.net

www.vertica.com

Technical documentation

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

dev.mysql.com/doc

docs.opengauss.org/en
gitee.com/opengauss/docs

postgis.net/documentation

vertica.com/documentation

Developer

Rocket Software (formerly Zumasys)

Oracle

since 2010, originally MySQL AB, then Sun

Huawei and openGauss community

OpenText

previously Micro Focus and Hewlett Packard

Initial release

1991

1995

2019

2005

Current release

5.7

8.4.0, April 2024

3.0, March 2022

3.4.2, February 2024

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL v2.0

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

C and C++

C, C++, Java

C++

Server operating systems

AIX
Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

optional

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

Embedded SQL for jBASE in BASIC

yes

with proprietary extensions

ANSI SQL 2011

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

.Net
Basic
Jabbascript
Java

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Java

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

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

user defined functions

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning (by range, list and hash)

yes

based on PostgreSQL

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Source-replica replication

yes

based on PostgreSQL

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Access rights can be defined down to the item level

Users with fine-grained authorization concept

no user groups or roles

Access rights for users, groups and roles according to SQL-standard

yes

based on PostgreSQL

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
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