DBMS > BaseX vs. EsgynDB vs. HEAVY.AI vs. JanusGraph vs. SpatiaLite

System Properties Comparison BaseX vs. EsgynDB vs. HEAVY.AI vs. JanusGraph vs. SpatiaLite

Editorial information provided by DB-Engines

Name

Description

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

A Graph DBMS optimized for distributed clusters

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

Spatial extension of SQLite

Primary database model

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Website

basex.org

www.esgyn.cn

github.com/heavyai/heavydb
www.heavy.ai

janusgraph.org

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

docs.basex.org

docs.heavy.ai

docs.janusgraph.org

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

BaseX GmbH

Esgyn

HEAVY.AI, Inc.

Linux Foundation; originally developed as Titan by Aurelius

Alessandro Furieri

Initial release

2007

2015

2016

2017

2008

Current release

11.0, June 2024

5.10, January 2022

0.6.3, February 2023

5.0.0, August 2020

License

Commercial or Open Source

Open Source

BSD license

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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

C++ and CUDA

Java

C++

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X
Unix
Windows

server-less

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

XQuery supports types

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

SQL

Support of SQL

yes

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

ADO.NET
JDBC
ODBC

JDBC
ODBC
Thrift
Vega

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

All languages supporting JDBC/ODBC/ADO.Net

All languages supporting JDBC/ODBC/Thrift
Python

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

yes

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

Multi-source replication

yes

none

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

multiple readers, single writer

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

In-memory capabilities

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

yes

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

XML Injection Attacks: What to Know About XPath, XQuery, XXE & More
18 May 2022, Hashed Out by The SSL Store™

9 Skills You Need to Become a Data Engineer
2 November 2022, KDnuggets

provided by Google News

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, Business Wire

HEAVY.AI Partners with Bain, Maxar, and Nvidia to Provide Digital Twins for Telecom Networks
16 February 2023, Datanami

Making the most of geospatial intelligence
14 April 2023, InfoWorld

The insideBIGDATA IMPACT 50 List for Q4 2023
11 October 2023, insideBIGDATA

provided by Google News

Database Deep Dives: JanusGraph
8 August 2019, IBM

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

From graph db to graph embedding. In 7 simple steps. | by Andy Greatorex
30 July 2020, Towards Data Science

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

provided by Google News

Share this page