DBMS > Kingbase vs. Microsoft Access vs. Oracle NoSQL vs. SAP Adaptive Server vs. Snowflake

System Properties Comparison Kingbase vs. Microsoft Access vs. Oracle NoSQL vs. SAP Adaptive Server vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

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

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	0.50
Rank	#257	Overall
	#119	Relational DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.kingbase.com.cn

www.microsoft.com/en-us/microsoft-365/access

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

www.sap.com/products/technology-platform/sybase-ase.html

www.snowflake.com

Technical documentation

developer.microsoft.com/en-us/access

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

help.sap.com/docs/SAP_ASE

docs.snowflake.net/manuals/index.html

Developer

BeiJing KINGBASE Information technologies inc.

Microsoft

Oracle

SAP, Sybase

Snowflake Computing Inc.

Initial release

1999

1992

2011

1987

2014

Current release

V8.0, August 2021

1902 (16.0.11328.20222), March 2019

24.1, May 2024

16.0

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

Open Source

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

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and Java

C++

Java

C and C++

Server operating systems

Linux
Windows

Windows

Not a real database server, but making use of DLLs

Linux
Solaris SPARC/x86

AIX
HP-UX
Linux
Solaris
Unix
Windows

hosted

Data scheme

yes

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

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

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

SQL

Support of SQL

Standard with numerous extensions

yes

but not compliant to any SQL standard

SQL-like DML and DDL statements

yes

APIs and other access methods

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

ADO.NET
DAO
ODBC
OLE DB

RESTful HTTP API

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

CLI Client
JDBC
ODBC

Supported programming languages

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

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

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

C
C++
Cobol
Java
Java
Perl
PHP
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

since Access 2010 using the ACE-engine

Java and Transact-SQL

user defined functions

Triggers

yes

since Access 2010 using the ACE-engine

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

but no files for transaction logging

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

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

fine grained access rights according to SQL-standard

a simple user-level security was built in till version Access 2003

Access rights for users and roles

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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