DBMS > Elasticsearch vs. JanusGraph vs. JSqlDb

System Properties Comparison Elasticsearch vs. JanusGraph vs. JSqlDb

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Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

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

JavaScript Query Language Database, stores JavaScript objects and primitives

Primary database model

Search engine
Vector DBMS

Graph DBMS

Document store
Object oriented DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	123.81
Rank	#9	Overall
	#1	Search engines
	#1	Vector DBMS

Score	1.78
Rank	#127	Overall
	#10	Graph DBMS

Website

www.elastic.co/elasticsearch

janusgraph.org

jsqldb.org (offline)

Technical documentation

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

docs.janusgraph.org

Developer

Elastic

Linux Foundation; originally developed as Titan by Aurelius

Konrad von Backstrom

Initial release

2010

2017

2018

Current release

8.6, January 2023

1.0.0, October 2023

0.8, December 2018

License

Commercial or Open Source

Open Source

Elastic License

Open Source

Apache 2.0

Open Source

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
macOS
Windows

Data scheme

schema-free

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

yes

schema-free

Typing

predefined data types such as float or date

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Java API
RESTful HTTP/JSON API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

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

Clojure
Java
Python

JavaScript

Server-side scripts

Stored procedures

yes

functions in JavaScript

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)

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

via Faunus, a graph analytics engine

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

Foreign keys

Referential integrity

yes

Relationships in graphs

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

yes

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

yes

using RocksDB

In-memory capabilities

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

Memcached and Redis integration

User concepts

Access control

User authentification and security via Rexster Graph Server

More information provided by the system vendor

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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

show all

Recent citations in the news

OpenSearch 3.0 hits: First major release under Linux Foundation as it battles ElasticSearch for mindshare
7 May 2025, devclass

OpenSearch in 2025: Much more than an Elasticsearch fork
28 April 2025, InfoWorld

Amazon OpenSearch Service announces Standard and Extended Support dates for Elasticsearch and OpenSearch versions
7 November 2024, Amazon Web Services (AWS)

Elasticsearch Now Available as a Native Grounding Engine on Google Cloud’s Vertex AI Platform
9 April 2025, Business Wire

Elasticsearch Was Great, But Vector Databases Are the Future
18 November 2024, The New Stack

provided by Google News

Database Deep Dives: JanusGraph
8 August 2019, IBM

Update Nordstrom Builds Flexible Backend Ops with Kubernetes, Spark and JanusGraph
28 March 2022, InApps Technology

The year of the graph: Getting graphic, going native, reshaping the landscape
8 January 2018, ZDNET

Performance Tuning Your Titan Graph Database on AWS
14 December 2015, Amazon Web Services (AWS)

Advantages of graph databases: Easier data modeling, analytics
23 January 2019, TechTarget

provided by Google News

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