DBMS > Elasticsearch vs. LeanXcale vs. RDF4J vs. STSdb

System Properties Comparison Elasticsearch vs. LeanXcale vs. RDF4J vs. STSdb

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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 highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Search engine

Key-value store
Relational DBMS

RDF store

Key-value store

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

www.elastic.co/elasticsearch

www.leanxcale.com

rdf4j.org

github.com/STSSoft/STSdb4

Technical documentation

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

rdf4j.org/documentation

Developer

Elastic

LeanXcale

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

STS Soft SC

Initial release

2010

2015

2004

2011

Current release

8.6, January 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GPLv2, commercial license available

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

Windows

Data scheme

schema-free

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

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

through Apache Derby

APIs and other access methods

Java API
RESTful HTTP/JSON API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

.NET Client API

Supported programming languages

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

C
Java
Scala

Java
PHP
Python

C#
Java

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

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

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

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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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