DBMS > Graph Engine vs. JanusGraph vs. Linter vs. OpenTSDB

System Properties Comparison Graph Engine vs. JanusGraph vs. Linter vs. OpenTSDB

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Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A Graph DBMS optimized for distributed clusters

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

RDBMS for high security requirements

Scalable Time Series DBMS based on HBase

Primary database model

Graph DBMS
Key-value store

Graph DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.62
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	1.91
Rank	#135	Overall
	#12	Graph DBMS

Score	0.10
Rank	#350	Overall
	#153	Relational DBMS

Score	1.73
Rank	#147	Overall
	#12	Time Series DBMS

Website

Technical documentation

www.graphengine.io/docs/manual

docs.janusgraph.org

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

Developer

Microsoft

Linux Foundation; originally developed as Titan by Aurelius

relex.ru

currently maintained by Yahoo and other contributors

Initial release

2010

2017

1990

2011

Current release

0.6.3, February 2023

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

commercial

Open Source

LGPL

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

.NET and C

Java

C and C++

Java

Server operating systems

.NET

Linux
OS X
Unix
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

HTTP API
Telnet API

Supported programming languages

C#
C++
F#
Visual Basic

Clojure
Java
Python

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

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

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

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

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

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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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

show all

Recent citations in the news

Trinity
2 June 2023, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

How Google and Microsoft taught search to "understand" the Web
6 June 2012, Ars Technica

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

provided by Google News

Simple Deployment of a Graph Database: JanusGraph | by Edward Elson Kosasih
12 October 2020, Towards Data Science

Database Deep Dives: JanusGraph
8 August 2019, ibm.com

JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

Nordstrom Builds Flexible Backend Ops with Kubernetes, Spark and JanusGraph
3 October 2019, The New Stack

Compose for JanusGraph arrives on Bluemix
15 September 2017, ibm.com

provided by Google News

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

MapR to help admins peer into dense Hadoop clusters
28 June 2016, SiliconANGLE News

Comparing InfluxDB, TimescaleDB, and QuestDB Timeseries Databases
30 June 2021, Towards Data Science

A real-time processing revival – O'Reilly
1 April 2015, oreilly.com

provided by Google News

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