DBMS > DuckDB vs. Kingbase vs. Oracle NoSQL vs. SAP HANA

System Properties Comparison DuckDB vs. Kingbase vs. Oracle NoSQL vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

An embeddable, in-process, column-oriented SQL OLAP RDBMS

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

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	4.57
Rank	#74	Overall
	#40	Relational DBMS

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

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

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

duckdb.org

www.kingbase.com.cn

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

www.sap.com/products/hana.html

Technical documentation

duckdb.org/docs

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

help.sap.com/hana

Developer

BeiJing KINGBASE Information technologies inc.

Oracle

SAP

Initial release

2018

1999

2011

2010

Current release

0.10, February 2024

V8.0, August 2021

23.3, December 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

MIT License

commercial

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

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

C and Java

Java

Server operating systems

server-less

Linux
Windows

Linux
Solaris SPARC/x86

Appliance or cloud-service

Data scheme

yes

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

yes

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

yes

Standard with numerous extensions

SQL-like DML and DDL statements

yes

APIs and other access methods

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

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

RESTful HTTP API

JDBC
ODBC

Supported programming languages

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

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

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

Server-side scripts

Stored procedures

user defined functions

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

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

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

yes

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