DBMS > EXASOL vs. ReductStore vs. Transwarp KunDB

System Properties Comparison EXASOL vs. ReductStore vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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.

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

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	0.14
Rank	#341	Overall
	#149	Relational DBMS

Website

www.exasol.com

github.com/reductstore
www.reduct.store

www.transwarp.cn/en/product/kundb

Technical documentation

www.exasol.com/resources

www.reduct.store/docs

Developer

Exasol

ReductStore LLC

Transwarp

Initial release

2000

2023

Current release

1.9, March 2024

License

Commercial or Open Source

commercial

Open Source

Business Source License 1.1

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Rust

Server operating systems

Docker
Linux
macOS
Windows

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

HTTP API

Supported programming languages

Java
Lua
Python
R

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

user defined functions

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

yes

Hadoop integration

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

Access rights for users, groups and roles according to SQL-standard

yes

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More resources

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