DBMS > jBASE vs. Kingbase vs. Microsoft SQL Server vs. Riak KV vs. Vitess

System Properties Comparison jBASE vs. Kingbase vs. Microsoft SQL Server vs. Riak KV vs. Vitess

Editorial information provided by DB-Engines

Name

Description

A robust multi-value DBMS comprising development tools and middleware

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Microsofts flagship relational DBMS

Distributed, fault tolerant key-value store

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Multivalue DBMS

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

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

www.kingbase.com.cn

www.microsoft.com/en-us/sql-server

vitess.io

Technical documentation

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

learn.microsoft.com/en-US/sql/sql-server

www.tiot.jp/riak-docs/riak/kv/latest

vitess.io/docs

Developer

Rocket Software (formerly Zumasys)

BeiJing KINGBASE Information technologies inc.

Microsoft

OpenSource, formerly Basho Technologies

The Linux Foundation, PlanetScale

Initial release

1991

1999

1989

2009

2013

Current release

5.7

V8.0, August 2021

SQL Server 2022, November 2022

3.2.0, December 2022

15.0.2, December 2022

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache version 2, commercial enterprise edition

Open Source

Apache Version 2.0, commercial licenses 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 and Java

C++

Erlang

Server operating systems

AIX
Linux
Windows

Linux
Windows

Linux
OS X

Docker
Linux
macOS

Data scheme

schema-free

yes

schema-free

yes

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

restricted

yes

SQL

Support of SQL

Embedded SQL for jBASE in BASIC

Standard with numerous extensions

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP API
Native Erlang Interface

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

.Net
Basic
Jabbascript
Java

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

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

Server-side scripts

Stored procedures

yes

user defined functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Erlang

yes

proprietary syntax

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

fine grained access rights according to SQL-standard

yes, using Riak Security

Users with fine-grained authorization concept

no user groups or roles

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