DBMS > EsgynDB vs. OrigoDB vs. RethinkDB vs. RRDtool vs. SwayDB

System Properties Comparison EsgynDB vs. OrigoDB vs. RethinkDB vs. RRDtool vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

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

A fully ACID in-memory object graph database

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Document store

Time Series DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

www.esgyn.cn

origodb.com

rethinkdb.com

oss.oetiker.ch/rrdtool

swaydb.simer.au

Technical documentation

origodb.com/docs

rethinkdb.com/docs

oss.oetiker.ch/rrdtool/doc

Developer

Esgyn

Robert Friberg et al

The Linux Foundation

since July 2017

Tobias Oetiker

Simer Plaha

Initial release

2015

2009

under the name LiveDB

2009

1999

2018

Current release

2.4.1, August 2020

1.8.0, 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

GPL V2 and FLOSS

Open Source

GNU Affero GPL V3.0

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

C++

Implementations in Java (e.g. RRD4J) and C# available

Scala

Server operating systems

Linux

Linux
Windows

Linux
OS X
Windows

HP-UX
Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

yes

string, binary, float, bool, date, geometry

Numeric data only

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.

can be achieved using .NET

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

.NET Client API
HTTP API
LINQ

in-process shared library
Pipes

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Domain Events

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

Atomic single-document operations

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

by using the rrdcached daemon

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Role based authorization

yes

users and table-level permissions

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More resources

DB-Engines blog posts

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1 June 2015, Paul Andlinger

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