DBMS > EventStoreDB vs. Immudb vs. Transwarp KunDB

System Properties Comparison EventStoreDB vs. Immudb 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.

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

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

Primary database model

Event Store

Key-value store

Relational DBMS

Secondary database models

Relational DBMS

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

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	0.24
Rank	#305	Overall
	#43	Key-value stores

Score	0.10
Rank	#344	Overall
	#151	Relational DBMS

Website

www.eventstore.com

github.com/codenotary/immudb
immudb.io

www.transwarp.cn/en/product/kundb

Technical documentation

developers.eventstore.com

docs.immudb.io

Developer

Event Store Limited

Codenotary

Transwarp

Initial release

2012

2020

Current release

21.2, February 2021

1.2.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Server operating systems

Linux
Windows

BSD
Linux
macOS
Solaris
Windows
z/OS

Data scheme

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like syntax

yes

APIs and other access methods

gRPC protocol
PostgreSQL wire protocol

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

yes

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