DBMS > IBM Db2 Event Store vs. Immudb vs. OushuDB vs. ReductStore

System Properties Comparison IBM Db2 Event Store vs. Immudb vs. OushuDB vs. ReductStore

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

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

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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

Event Store
Time Series DBMS

Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

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

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

www.ibm.com/products/db2-event-store

github.com/codenotary/immudb
immudb.io

www.oushu.com/product/oushuDB

github.com/reductstore
www.reduct.store

Technical documentation

www.ibm.com/docs/en/db2-event-store

docs.immudb.io

www.oushu.com/documentation

www.reduct.store/docs

Developer

IBM

Codenotary

Oushu

ReductStore LLC

Initial release

2017

2020

2023

Current release

2.0

1.2.3, April 2022

4.0.1, August 2020

1.9, March 2024

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Apache Version 2.0

commercial

Open Source

Business Source License 1.1

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 and C++

C++, Rust

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux

Docker
Linux
macOS
Windows

Data scheme

yes

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

yes

through the embedded Spark runtime

SQL-like syntax

Full-featured ANSI SQL support

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

gRPC protocol
PostgreSQL wire protocol

JDBC
ODBC

HTTP API

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

.Net
Go
Java
JavaScript (Node.js)
Python

C
C++

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

No - written data is immutable

yes

Durability

Support for making data persistent

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

fine grained access rights according to SQL-standard

Kerberos, SSL and role based access

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