DBMS > Apache Jena - TDB vs. Brytlyt vs. GigaSpaces vs. JanusGraph vs. Microsoft SQL Server

System Properties Comparison Apache Jena - TDB vs. Brytlyt vs. GigaSpaces vs. JanusGraph vs. Microsoft SQL Server

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

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

A Graph DBMS optimized for distributed clusters

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

Microsofts flagship relational DBMS

Primary database model

RDF store

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Graph DBMS

Relational DBMS

Secondary database models

Graph DBMS
Search engine

Document store
Graph DBMS
Spatial DBMS

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

Score	3.62
Rank	#83	Overall
	#3	RDF stores

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

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

brytlyt.io

www.gigaspaces.com

janusgraph.org

www.microsoft.com/en-us/sql-server

Technical documentation

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

docs.brytlyt.io

docs.gigaspaces.com/latest/landing.html

docs.janusgraph.org

learn.microsoft.com/en-US/sql/sql-server

Developer

Apache Software Foundation

originally developed by HP Labs

Brytlyt

Gigaspaces Technologies

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

Initial release

2000

2016

2000

2017

1989

Current release

4.9.0, July 2023

5.0, August 2023

15.5, September 2020

0.6.3, February 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache 2.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C, C++ and CUDA

Java, C++, .Net

Java

C++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

Linux
macOS
Solaris
Windows

Linux
OS X
Unix
Windows

Linux
Windows

Data scheme

yes

RDF Schemas

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

yes

specific XML-type available, but no XML query functionality.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-99 for query and DML statements

yes

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Java

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
C++
Java
Python
Scala

Clojure
Java
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

user defined functions

in PL/pgSQL

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

via event handler

yes

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

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

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency
Immediate 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

ACID

TDB Transactions

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

Access control via Jena Security

fine grained access rights according to SQL-standard

Role-based access control

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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