DBMS > Amazon DynamoDB vs. Google BigQuery vs. Microsoft SQL Server vs. Oracle NoSQL vs. RDF4J

System Properties Comparison Amazon DynamoDB vs. Google BigQuery vs. Microsoft SQL Server vs. Oracle NoSQL vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Large scale data warehouse service with append-only tables

Microsofts flagship relational DBMS

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Key-value store
Relational DBMS

RDF store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

aws.amazon.com/dynamodb

cloud.google.com/bigquery

www.microsoft.com/en-us/sql-server

www.oracle.com/database/nosql/technologies/nosql

rdf4j.org

Technical documentation

docs.aws.amazon.com/dynamodb

cloud.google.com/bigquery/docs

learn.microsoft.com/en-US/sql/sql-server

docs.oracle.com/en/database/other-databases/nosql-database/index.html

rdf4j.org/documentation

Developer

Amazon

Google

Microsoft

Oracle

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2012

2010

1989

2011

2004

Current release

SQL Server 2022, November 2022

24.1, May 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

restricted free version is available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

hosted

Linux
Windows

Linux
Solaris SPARC/x86

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

optional

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

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C#
Go
Java
JavaScript (Node.js)
Python

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

Since BigQuery is designed for querying data

ACID

configurable

ACID within a storage node (=shard)

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

off heap cache

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

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

Access rights for users and roles

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