DBMS > EventStoreDB vs. GBase vs. GridGain vs. Transwarp KunDB

System Properties Comparison EventStoreDB vs. GBase vs. GridGain vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

GridGain is an in-memory computing platform, built on Apache Ignite

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Event Store

Relational DBMS

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

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

Score	1.07
Rank	#181	Overall
	#1	Event Stores

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	0.04
Rank	#362	Overall
	#154	Relational DBMS

Website

www.eventstore.com

www.gbase.cn

www.gridgain.com

www.transwarp.cn/en/product/kundb

Technical documentation

developers.eventstore.com

www.gridgain.com/docs/index.html

Developer

Event Store Limited

General Data Technology Co., Ltd.

GridGain Systems, Inc.

Transwarp

Initial release

2012

2004

2007

Current release

21.2, February 2021

GBase 8a, GBase 8s, GBase 8c

GridGain 8.5.1

License

Commercial or Open Source

Open Source

commercial

commercial, open source

commercial

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, Java, Python

Java, C++, .Net, Python, REST, SQL

Server operating systems

Linux
Windows

Linux

Linux
OS X
Solaris
Windows
z/OS

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

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

ADO.NET
C API
JDBC
ODBC

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

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

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

yes

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

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

yes

Role-based access control
Security Hooks for custom implementations

yes

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