DBMS > EXASOL vs. GraphDB vs. RDF4J vs. Redis vs. SQLite

System Properties Comparison EXASOL vs. GraphDB vs. RDF4J vs. Redis vs. SQLite

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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.

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

Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments

Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies.

Widely used embeddable, in-process RDBMS

Primary database model

Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence

Relational DBMS

Secondary database models

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

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

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	3.25
Rank	#91	Overall
	#7	Graph DBMS
	#4	RDF stores

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	155.94
Rank	#6	Overall
	#1	Key-value stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

Technical documentation

www.exasol.com/resources

graphdb.ontotext.com/documentation

rdf4j.org/documentation

docs.redis.com/latest/index.html
redis.io/docs

www.sqlite.org/docs.html

Social network pages

Developer

Exasol

Ontotext

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

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Dwayne Richard Hipp

Initial release

2000

2004

2009

2000

Current release

10.4, October 2023

7.2.5, May 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

source-available extensions (modules), commercial licenses for Redis Enterprise

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.

Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.

Implementation language

Java

Server operating systems

All OS with a Java VM
Linux
OS X
Windows

Linux
OS X
Unix
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

server-less

Data scheme

yes

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

yes

RDF Schemas

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

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

yes

with RediSearch module

yes

SQL

Support of SQL

yes

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

with RediSQL module

yes

SQL-92 is not fully supported

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Java
Lua
Python
R

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

Java
PHP
Python

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

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

user defined functions

well-defined plugin interfaces; JavaScript server-side extensibility

yes

Lua; Redis Functions coming in Redis 7 (slides and Github)

Triggers

yes

publish/subscribe channels provide some trigger functionality; RedisGears

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Automatic hash-based sharding with support for hash-tags for manual sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

Foreign keys

Referential integrity

yes

Constraint checking

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Atomic execution of command blocks and scripts and optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

via file-system locks

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

Access rights for users, groups and roles according to SQL-standard

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.

Access Control Lists (ACLs): redis.io/docs/management/security/acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/docs/management/security/encryption
Password-based authentication

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
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Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
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Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
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Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
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Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
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Licensing and pricing models

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

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6 June 2024

Matching Skills and Candidates with Graph RAG
31 May 2024

A Triple Store RAG Retriever
29 May 2024

Integrating GraphDB with Relational Database Systems
23 May 2024

Understanding the Graph Center of Excellence
17 May 2024

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