DBMS > OpenTSDB vs. RDF4J vs. Realm vs. VoltDB

System Properties Comparison OpenTSDB vs. RDF4J vs. Realm vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Scalable Time Series DBMS based on HBase

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

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

Score	1.73
Rank	#147	Overall
	#12	Time Series DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	7.71
Rank	#52	Overall
	#9	Document stores

Score	1.46
Rank	#159	Overall
	#74	Relational DBMS

Website

Technical documentation

opentsdb.net/docs/build/html/index.html

rdf4j.org/documentation

realm.io/docs

docs.voltdb.com

Developer

currently maintained by Yahoo and other contributors

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

Realm, acquired by MongoDB in May 2019

VoltDB Inc.

Initial release

2011

2004

2014

2010

Current release

11.3, April 2022

License

Commercial or Open Source

Open Source

LGPL

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java

Java, C++

Server operating systems

Linux
Windows

Linux
OS X
Unix
Windows

Android
Backend: server-less
iOS
Windows

Linux
OS X

for development

Data scheme

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

numeric data for metrics, strings for tags

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

only a subset of SQL 99

APIs and other access methods

HTTP API
Telnet API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Erlang
Go
Java
Python
R
Ruby

Java
PHP
Python

.Net
Java

with Android only
Objective-C
React Native
Swift

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

runs within the applications so server-side scripts are unnecessary

Java

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on HBase

none

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

Immediate Consistency

based on HBase

Immediate Consistency

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

Snapshots and command logging

In-memory capabilities

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

yes

In-Memory realm

User concepts

Access control

yes

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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