DBMS > JanusGraph vs. Newts vs. Quasardb vs. Riak TS vs. SQLite

System Properties Comparison JanusGraph vs. Newts vs. Quasardb vs. Riak TS vs. SQLite

Editorial information provided by DB-Engines

Name

Description

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Time Series DBMS based on Cassandra

Distributed, high-performance timeseries database

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Widely used embeddable, in-process RDBMS

Primary database model

Graph DBMS

Time Series DBMS

Relational DBMS

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

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

janusgraph.org

opennms.github.io/newts

quasar.ai

www.sqlite.org

Technical documentation

docs.janusgraph.org

github.com/OpenNMS/newts/wiki

doc.quasar.ai/master

www.tiot.jp/riak-docs/riak/ts/latest

www.sqlite.org/docs.html

Developer

Linux Foundation; originally developed as Titan by Aurelius

OpenNMS Group

quasardb

Open Source, formerly Basho Technologies

Dwayne Richard Hipp

Initial release

2017

2014

2009

2015

2000

Current release

0.6.3, February 2023

3.14.1, January 2024

3.0.0, September 2022

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Public Domain

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

C++

Erlang

Server operating systems

Linux
OS X
Unix
Windows

Linux
OS X
Windows

BSD
Linux
OS X
Windows

Linux
OS X

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

integer and binary

yes

not rigid because of 'dynamic typing' concept.

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

with tags

restricted

yes

SQL

Support of SQL

SQL-like query language

yes, limited

yes

SQL-92 is not fully supported

APIs and other access methods

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP REST
Java API

HTTP API

HTTP API
Native Erlang Interface

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Clojure
Java
Python

Java

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

based on Cassandra

Sharding

consistent hashing

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Source-replica replication with selectable replication factor

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

links between datasets can be stored

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

User authentification and security via Rexster Graph Server

Cryptographically strong user authentication and audit trail

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