DBMS > BoltDB vs. EsgynDB vs. KairosDB vs. RDF4J vs. ReductStore

System Properties Comparison BoltDB vs. EsgynDB vs. KairosDB vs. RDF4J vs. ReductStore

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Distributed Time Series DBMS based on Cassandra or H2

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

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

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

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Website

github.com/boltdb/bolt

www.esgyn.cn

github.com/kairosdb/kairosdb

rdf4j.org

github.com/reductstore
www.reduct.store

Technical documentation

kairosdb.github.io

rdf4j.org/documentation

www.reduct.store/docs

Developer

Esgyn

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

ReductStore LLC

Initial release

2013

2015

2013

2004

2023

Current release

1.2.2, November 2018

1.9, March 2024

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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++, Java

Java

C++, Rust

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Docker
Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

yes

RDF Schemas

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

ADO.NET
JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript

Node.js
PHP
Python

Java
PHP
Python

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

selectable replication factor

based on Cassandra

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

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