DBMS > Apache Jena - TDB vs. GridGain vs. Microsoft Azure Synapse Analytics

System Properties Comparison Apache Jena - TDB vs. GridGain vs. Microsoft Azure Synapse Analytics

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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

GridGain is an in-memory computing platform, built on Apache Ignite

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Primary database model

RDF store

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

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

Score	2.91
Rank	#93	Overall
	#3	RDF stores

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Website

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

www.gridgain.com

azure.microsoft.com/services/synapse-analytics

Technical documentation

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

www.gridgain.com/docs/index.html

docs.microsoft.com/azure/synapse-analytics

Developer

Apache Software Foundation

originally developed by HP Labs

GridGain Systems, Inc.

Microsoft

Initial release

2000

2007

2016

Current release

4.9.0, July 2023

GridGain 8.5.1

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

commercial, open source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Java, C++, .Net, Python, REST, SQL

C++

Server operating systems

All OS with a Java VM

Linux
OS X
Solaris
Windows
z/OS

hosted

Data scheme

yes

RDF Schemas

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

Secondary indexes

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC

Supported programming languages

Java

C#
C++
Java
PHP
Python
Ruby
Scala

C#
Java
PHP

Server-side scripts

Stored procedures

yes

yes (compute grid and cache interceptors can be used instead)

Transact SQL

Triggers

yes

via event handler

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes (replicated cache)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

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

Role-based access control
Security Hooks for custom implementations

yes

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