DBMS > DataFS vs. GBase vs. Ignite vs. Microsoft Azure AI Search vs. SAP HANA

System Properties Comparison DataFS vs. GBase vs. Ignite vs. Microsoft Azure AI Search vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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.

Search-as-a-service for web and mobile app development

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

Primary database model

Object oriented DBMS

Relational DBMS

Key-value store
Relational DBMS

Search engine

Relational DBMS

Secondary database models

Graph DBMS

Vector 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	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

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

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

newdatabase.com

www.gbase.cn

ignite.apache.org

azure.microsoft.com/en-us/services/search

www.sap.com/products/hana.html

Technical documentation

dev.mobiland.com/Overview.xsp

apacheignite.readme.io/docs

learn.microsoft.com/en-us/azure/search

help.sap.com/hana

Developer

Mobiland AG

General Data Technology Co., Ltd.

Apache Software Foundation

Microsoft

SAP

Initial release

2018

2004

2015

2010

Current release

1.1.263, October 2022

GBase 8a, GBase 8s, GBase 8c

Apache Ignite 2.6

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

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

Server operating systems

Windows

Linux

Linux
OS X
Solaris
Windows

hosted

Appliance or cloud-service

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

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

yes

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
C API
JDBC
ODBC

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

RESTful HTTP API

JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
VB.Net

C#
C++
Java
PHP
Python
Ruby
Scala

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

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

SQLScript, R

Triggers

no, except callback-events from server when changes happened

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

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

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

yes

Implicit feature of the cloud service

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

Windows-Profile

yes

Security Hooks for custom implementations

yes

using Azure authentication

yes

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