DBMS > Amazon Redshift vs. Apache Jena - TDB vs. Google Cloud Datastore

System Properties Comparison Amazon Redshift vs. Apache Jena - TDB vs. Google Cloud Datastore

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

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

Primary database model

Relational DBMS

RDF store

Document store

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	2.91
Rank	#93	Overall
	#3	RDF stores

Score	4.13
Rank	#71	Overall
	#12	Document stores

Website

aws.amazon.com/redshift

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

cloud.google.com/datastore

Technical documentation

docs.aws.amazon.com/redshift

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

cloud.google.com/datastore/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

originally developed by HP Labs

Google

Initial release

2012

2000

2008

Current release

4.9.0, July 2023

License

Commercial or Open Source

commercial

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

Server operating systems

hosted

All OS with a Java VM

hosted

Data scheme

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

yes, details here

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language (GQL)

APIs and other access methods

JDBC
ODBC

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

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

Supported programming languages

All languages supporting JDBC/ODBC

Java

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes

using Google App Engine

Triggers

yes

via event handler

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication using Paxos

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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.

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

TDB Transactions

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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

fine grained access rights according to SQL-standard

Access control via Jena Security

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

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