DBMS > Elasticsearch vs. JanusGraph vs. Oracle NoSQL

System Properties Comparison Elasticsearch vs. JanusGraph vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

A Graph DBMS optimized for distributed clusters

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

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

Primary database model

Search engine

Graph DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	130.82
Rank	#8	Overall
	#1	Search engines

Score	1.89
Rank	#128	Overall
	#12	Graph DBMS

Score	2.93
Rank	#94	Overall
	#17	Document stores
	#14	Key-value stores
	#50	Relational DBMS

Website

www.elastic.co/elasticsearch

janusgraph.org

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

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

docs.janusgraph.org

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

Developer

Elastic

Linux Foundation; originally developed as Titan by Aurelius

Oracle

Initial release

2010

2017

2011

Current release

8.6, January 2023

0.6.3, February 2023

24.1, May 2024

License

Commercial or Open Source

Open Source

Elastic License

Open Source

Apache 2.0

Open Source

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

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

All OS with a Java VM

Linux
OS X
Unix
Windows

Linux
Solaris SPARC/x86

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

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

Typing

predefined data types such as float or date

yes

optional

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

Java API
RESTful HTTP/JSON API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

RESTful HTTP API

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
Java
Python

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

Server-side scripts

Stored procedures

yes

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

via Faunus, a graph analytics engine

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency
Immediate Consistency

depending on configuration

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)

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.

Memcached and Redis integration

yes

off heap cache

User concepts

Access control

User authentification and security via Rexster Graph Server

Access rights for users and roles

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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2017
2 January 2018, Paul Andlinger, Matthias Gelbmann

Elasticsearch moved into the top 10 most popular database management systems
3 July 2017, Matthias Gelbmann

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

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Recent citations in the news

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24 July 2024, SiliconANGLE News

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26 March 2024, insider.govtech.com

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10 July 2024, Business Wire

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3 October 2019, The New Stack

Compose for JanusGraph arrives on Bluemix
15 September 2017, IBM

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