DBMS > Amazon Aurora vs. Apache Jena - TDB vs. Microsoft Azure Cosmos DB vs. Splice Machine

System Properties Comparison Amazon Aurora vs. Apache Jena - TDB vs. Microsoft Azure Cosmos DB vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

A RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework

Globally distributed, horizontally scalable, multi-model database service

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Relational DBMS

RDF store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Document store

Spatial DBMS

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	3.75
Rank	#84	Overall
	#3	RDF stores

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

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

aws.amazon.com/rds/aurora

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

azure.microsoft.com/services/cosmos-db

splicemachine.com

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

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

learn.microsoft.com/azure/cosmos-db

splicemachine.com/how-it-works

Developer

Amazon

Apache Software Foundation

originally developed by HP Labs

Microsoft

Splice Machine

Initial release

2015

2000

2014

Current release

4.9.0, July 2023

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

Apache License, Version 2.0

commercial

Open Source

AGPL 3.0, commercial license 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

hosted

All OS with a Java VM

hosted

Linux
OS X
Solaris
Windows

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.

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

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

JDBC
Native Spark Datasource
ODBC

Supported programming languages

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

Java

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

JavaScript

yes

Java

Triggers

yes

via event handler

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Implicit feature of the cloud service

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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*

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

TDB Transactions

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Access control via Jena Security

Access rights can be defined down to the item level

Access rights for users, groups and roles according to SQL-standard

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