DBMS > Apache Jena - TDB vs. Firebase Realtime Database vs. Microsoft Azure Cosmos DB vs. Vitess

System Properties Comparison Apache Jena - TDB vs. Firebase Realtime Database vs. Microsoft Azure Cosmos DB vs. Vitess

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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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Globally distributed, horizontally scalable, multi-model database service

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

RDF store

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	3.62
Rank	#83	Overall
	#3	RDF stores

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

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

firebase.google.com/products/realtime-database

azure.microsoft.com/services/cosmos-db

vitess.io

Technical documentation

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

firebase.google.com/docs/database

learn.microsoft.com/azure/cosmos-db

vitess.io/docs

Developer

Apache Software Foundation

originally developed by HP Labs

Google

acquired by Google 2014

Microsoft

The Linux Foundation, PlanetScale

Initial release

2000

2012

2014

2013

Current release

4.9.0, July 2023

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

commercial

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

All OS with a Java VM

hosted

Docker
Linux
macOS

Data scheme

yes

RDF Schemas

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

Android
iOS
JavaScript API
RESTful HTTP API

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

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Java

Java
JavaScript
Objective-C

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

limited functionality with using 'rules'

JavaScript

yes

proprietary syntax

Triggers

yes

via event handler

Callbacks are triggered when data changes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

TDB Transactions

yes

Multi-item ACID transactions with snapshot isolation within a partition

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

yes, based on authentication and database rules

Access rights can be defined down to the item level

Users with fine-grained authorization concept

no user groups or roles

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