DBMS > Apache Jena - TDB vs. Faircom DB vs. Google Cloud Datastore vs. H2 vs. Microsoft Azure Cosmos DB

System Properties Comparison Apache Jena - TDB vs. Faircom DB vs. Google Cloud Datastore vs. H2 vs. Microsoft Azure Cosmos DB

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

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

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Globally distributed, horizontally scalable, multi-model database service

Primary database model

RDF store

Key-value store
Relational DBMS

Document store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	3.75
Rank	#84	Overall
	#3	RDF stores

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

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

www.faircom.com/products/faircom-db

cloud.google.com/datastore

www.h2database.com

azure.microsoft.com/services/cosmos-db

Technical documentation

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

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

cloud.google.com/datastore/docs

www.h2database.com/html/main.html

learn.microsoft.com/azure/cosmos-db

Developer

Apache Software Foundation

originally developed by HP Labs

FairCom Corporation

Google

Thomas Mueller

Microsoft

Initial release

2000

1979

2008

2005

2014

Current release

4.9.0, July 2023

V12, November 2020

2.2.220, July 2023

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

commercial

Restricted, free version available

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

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

ANSI C, C++

Java

Server operating systems

All OS with a Java VM

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

easily portable to other OSs

hosted

All OS with a Java VM

hosted

Data scheme

yes

RDF Schemas

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

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

yes, details here

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

SQL-like query language (GQL)

yes

SQL-like query language

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

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

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

JDBC
ODBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

Java

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

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

using Google App Engine

Java Stored Procedures and User-Defined Functions

JavaScript

Triggers

yes

via event handler

yes

Callbacks using the Google Apps Engine

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Multi-source replication using Paxos

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

TDB Transactions

tunable from ACID to Eventually Consistent

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

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

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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