DBMS > Geode vs. ReductStore vs. Transbase

System Properties Comparison Geode vs. ReductStore vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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.

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

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

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

geode.apache.org

github.com/reductstore
www.reduct.store

www.transaction.de/en/products/transbase.html

Technical documentation

geode.apache.org/docs

www.reduct.store/docs

www.transaction.de/en/products/transbase/features.html

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

ReductStore LLC

Transaction Software GmbH

Initial release

2002

2023

1987

Current release

1.1, February 2017

1.9, March 2024

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Business Source License 1.1

commercial

free development license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++, Rust

C and C++

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

Docker
Linux
macOS
Windows

FreeBSD
Linux
macOS
Solaris
Windows

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 query language (OQL)

yes

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

C++
JavaScript (Node.js)
Python
Rust

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes, on a single node

yes

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 per client and object definable

fine grained access rights according to SQL-standard

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