DBMS > Apache Jena - TDB vs. Google BigQuery vs. Ingres vs. Microsoft Azure Synapse Analytics vs. TimesTen

System Properties Comparison Apache Jena - TDB vs. Google BigQuery vs. Ingres vs. Microsoft Azure Synapse Analytics vs. TimesTen

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

Large scale data warehouse service with append-only tables

Well established RDBMS

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

In-Memory RDBMS compatible to Oracle

Primary database model

RDF store

Relational DBMS

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

Score	3.62
Rank	#83	Overall
	#3	RDF stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

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

cloud.google.com/bigquery

www.actian.com/databases/ingres

azure.microsoft.com/services/synapse-analytics

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

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

cloud.google.com/bigquery/docs

docs.actian.com/ingres

docs.microsoft.com/azure/synapse-analytics

docs.oracle.com/database/timesten-18.1

Developer

Apache Software Foundation

originally developed by HP Labs

Google

Actian Corporation

Microsoft

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2000

2010

1974

originally developed at University Berkely in early 1970s

2016

1998

Current release

4.9.0, July 2023

11.2, May 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

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

C++

Server operating systems

All OS with a Java VM

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
PHP

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

Transact SQL

PL/SQL

Triggers

yes

via event handler

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Ingres Replicator

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

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

yes

Transaction concepts

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

ACID

TDB Transactions

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.