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

System Properties Comparison EventStoreDB vs. Firebolt vs. GBase 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.

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

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

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

Primary database model

Event Store

Relational DBMS

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

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	1.90
Rank	#134	Overall
	#62	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.10
Rank	#344	Overall
	#151	Relational DBMS

Website

www.eventstore.com

www.firebolt.io

www.gbase.cn

www.transwarp.cn/en/product/kundb

Technical documentation

developers.eventstore.com

docs.firebolt.io

Developer

Event Store Limited

Firebolt Analytics Inc.

General Data Technology Co., Ltd.

Transwarp

Initial release

2012

2020

2004

Current release

21.2, February 2021

GBase 8a, GBase 8s, GBase 8c

License

Commercial or Open Source

Open Source

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, Java, Python

Server operating systems

Linux
Windows

hosted

Linux

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

yes

Standard with numerous extensions

yes

APIs and other access methods

.Net
ODBC
RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

Supported programming languages

Go
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

User concepts

Access control

yes

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