DBMS > Apache Jena - TDB vs. Dragonfly vs. Faircom DB vs. SQLite

System Properties Comparison Apache Jena - TDB vs. Dragonfly vs. Faircom DB vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

A RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Widely used embeddable, in-process RDBMS

Primary database model

RDF store

Key-value store

Key-value store
Relational DBMS

Relational DBMS

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

Score	3.85
Rank	#86	Overall
	#3	RDF stores

Score	0.42
Rank	#271	Overall
	#38	Key-value stores

Score	0.24
Rank	#311	Overall
	#44	Key-value stores
	#140	Relational DBMS

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Website

jena.apache.org/documentation/tdb/index.html

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.faircom.com/products/faircom-db

www.sqlite.org

Technical documentation

jena.apache.org/documentation/tdb/index.html

www.dragonflydb.io/docs

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

www.sqlite.org/docs.html

Developer

Apache Software Foundation

originally developed by HP Labs

DragonflyDB team and community contributors

FairCom Corporation

Dwayne Richard Hipp

Initial release

2000

2023

1979

2000

Current release

4.9.0, July 2023

1.0, March 2023

V12, November 2020

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

Open Source

BSL 1.1

commercial

Restricted, free version available

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

ANSI C, C++

Server operating systems

All OS with a Java VM

Linux

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

server-less

Data scheme

yes

RDF Schemas

scheme-free

schema free, schema optional, schema required, partial schema,

yes

dynamic column types

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

yes, ANSI SQL Types, JSON, typed binary structures

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

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

yes

SQL-92 is not fully supported

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Java

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
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

yes

Lua

yes

.Net, JavaScript, C/C++

Triggers

yes

via event handler

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

TDB Transactions

Atomic execution of command blocks and scripts

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

via file-system locks

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

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 control via Jena Security

Password-based authentication

Fine grained access rights according to SQL-standard with additional protections for files

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