DBMS > JanusGraph vs. Machbase Neo vs. Oracle NoSQL vs. Splunk

System Properties Comparison JanusGraph vs. Machbase Neo vs. Oracle NoSQL vs. Splunk

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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

TimeSeries DBMS for AIoT and BigData

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Analytics Platform for Big Data

Primary database model

Graph DBMS

Time Series DBMS

Document store
Key-value store
Relational DBMS

Search engine

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

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

janusgraph.org

machbase.com

www.oracle.com/database/nosql/technologies/nosql

www.splunk.com

Technical documentation

docs.janusgraph.org

machbase.com/dbms

docs.oracle.com/en/database/other-databases/nosql-database/index.html

docs.splunk.com/Documentation/Splunk

Developer

Linux Foundation; originally developed as Titan by Aurelius

Machbase

Oracle

Splunk Inc.

Initial release

2017

2013

2011

2003

Current release

0.6.3, February 2023

V8.0, August 2023

24.1, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free test version available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

Limited free edition and free developer edition available

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

Server operating systems

Linux
OS X
Unix
Windows

Linux
macOS
Windows

Linux
Solaris SPARC/x86

Linux
OS X
Solaris
Windows

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

optional

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

Splunk Search Processing Language for search commands

APIs and other access methods

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

RESTful HTTP API

HTTP REST

Supported programming languages

Clojure
Java
Python

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C
C#
Go
Java
JavaScript (Node.js)
Python

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Multi-source replication

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

depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

volatile and lookup table

yes

off heap cache

User concepts

Access control

User authentification and security via Rexster Graph Server

simple password-based access control

Access rights for users and roles

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More resources

DB-Engines blog posts

Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

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Recent citations in the news

Simple Deployment of a Graph Database: JanusGraph
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

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provided by Google News

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