DBMS > EventStoreDB vs. LMDB vs. OushuDB

System Properties Comparison EventStoreDB vs. LMDB vs. OushuDB

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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.

A high performant, light-weight, embedded key-value database library

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

Event Store

Key-value store

Relational DBMS

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

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Website

www.eventstore.com

www.symas.com/symas-embedded-database-lmdb

www.oushu.com/product/oushuDB

Technical documentation

developers.eventstore.com

www.lmdb.tech/doc

www.oushu.com/documentation

Developer

Event Store Limited

Symas

Oushu

Initial release

2012

2011

Current release

21.2, February 2021

0.9.32, January 2024

4.0.1, August 2020

License

Commercial or Open Source

Open Source

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

Linux
Unix
Windows

Linux

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

Full-featured ANSI SQL support

APIs and other access methods

JDBC
ODBC

Supported programming languages

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

C
C++

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

Kerberos, SSL and role based access

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