DBMS > Elasticsearch vs. EsgynDB vs. JanusGraph vs. XTDB

System Properties Comparison Elasticsearch vs. EsgynDB vs. JanusGraph vs. XTDB

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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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A Graph DBMS optimized for distributed clusters

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	128.79
Rank	#8	Overall
	#1	Search engines

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	1.85
Rank	#134	Overall
	#12	Graph DBMS

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

www.elastic.co/elasticsearch

www.esgyn.cn

janusgraph.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

docs.janusgraph.org

www.xtdb.com/docs

Developer

Elastic

Esgyn

Linux Foundation; originally developed as Titan by Aurelius

Juxt Ltd.

Initial release

2010

2015

2017

2019

Current release

8.6, January 2023

1.0.0, October 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

Apache 2.0

Open Source

MIT License

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++, Java

Java

Clojure

Server operating systems

All OS with a Java VM

Linux

Linux
OS X
Unix
Windows

All OS with a Java 8 (and higher) VM
Linux

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

yes, extensible-data-notation format

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

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP REST
JDBC

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

Clojure
Java
Python

Clojure
Java

Server-side scripts

Stored procedures

yes

Java 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)

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

yes

yes, each node contains all data

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

Immediate Consistency

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, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

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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

Elasticsearch will be open source again as CTO declares changed landscape
2 September 2024, DevClass

Unsecured Elasticsearch cluster exposes over 3M vehicle records
18 September 2024, SC Media

The Elasticsearch cloud now subject to open-source licence
3 September 2024, TechHQ

Elasticsearch Open Inference API Extends Support for Hugging Face Models with Semantic Text
12 September 2024, Yahoo Finance

Elastic Announces Open Source License for Elasticsearch and Kibana Source Code
29 August 2024, Business Wire

provided by Google 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

provided by Google News

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