DBMS > BaseX vs. Elasticsearch vs. GraphDB vs. SQLite

System Properties Comparison BaseX vs. Elasticsearch vs. GraphDB vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

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

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-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

Widely used embeddable, in-process RDBMS

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	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	3.32
Rank	#91	Overall
	#6	Graph DBMS
	#4	RDF stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

basex.org

www.elastic.co/elasticsearch

www.ontotext.com

www.sqlite.org

Technical documentation

docs.basex.org

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

graphdb.ontotext.com/documentation

www.sqlite.org/docs.html

Social network pages

Developer

BaseX GmbH

Elastic

Ontotext

Dwayne Richard Hipp

Initial release

2007

2010

2000

Current release

10.7, August 2023

8.6, January 2023

10.4, October 2023

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

BSD license

Open Source

Elastic License

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

Public Domain

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
Windows

All OS with a Java VM

All OS with a Java VM
Linux
OS X
Windows

server-less

Data scheme

schema-free

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

schema-free and OWL/RDFS-schema support; RDF shapes

yes

dynamic column types

Typing

predefined data types such as float or date

XQuery supports types

yes

not rigid because of 'dynamic typing' concept.

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, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

yes

SQL

Support of SQL

SQL-like query language

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

yes

SQL-92 is not fully supported

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

Java API
RESTful HTTP/JSON API

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

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

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

well-defined plugin interfaces; JavaScript server-side extensibility

Triggers

yes

via events

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

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 (configurable in cluster mode per master or individual client request)

Foreign keys

Referential integrity

yes

Constraint checking

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

via file-system locks

Durability

Support for making data persistent

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

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

News

Migrating From LPG to RDF Graph Model
8 May 2024

Case study: Policy Enforcement Automation With Semantics
2 May 2024

Okay, RAG… We Have a Problem
26 April 2024

Scaling Understanding with the Help of Feedback Loops, Knowledge Graphs and NLP
19 April 2024

How Knowledge Graphs Power Data Mesh and Data Fabric
10 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.