DBMS > Citus vs. GBase vs. Ignite vs. Kingbase vs. SAP HANA

System Properties Comparison Citus vs. GBase vs. Ignite vs. Kingbase vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

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

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

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store

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	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

www.sap.com/products/hana.html

Technical documentation

docs.citusdata.com

apacheignite.readme.io/docs

help.sap.com/hana

Developer

General Data Technology Co., Ltd.

Apache Software Foundation

BeiJing KINGBASE Information technologies inc.

SAP

Initial release

2010

2004

2015

1999

2010

Current release

8.1, December 2018

GBase 8a, GBase 8s, GBase 8c

Apache Ignite 2.6

V8.0, August 2021

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

commercial

Open Source

Apache 2.0

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, Java, Python

C++, Java, .Net

C and Java

Server operating systems

Linux

Linux
OS X
Solaris
Windows

Linux
Windows

Appliance or cloud-service

Data scheme

yes

Typing

predefined data types such as float or date

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

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

Standard with numerous extensions

ANSI-99 for query and DML statements, subset of DDL

Standard with numerous extensions

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
C API
JDBC
ODBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

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

JDBC
ODBC

Supported programming languages

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

C#
C++
Java
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

user defined functions

yes (compute grid and cache interceptors can be used instead)

user defined functions

SQLScript, R

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

yes

yes (replicated cache)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

yes

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