DBMS > Amazon SimpleDB vs. Google BigQuery vs. Stardog vs. TerminusDB vs. Yanza

System Properties Comparison Amazon SimpleDB vs. Google BigQuery vs. Stardog vs. TerminusDB vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

Large scale data warehouse service with append-only tables

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Document store
RDF store

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

Score	1.85
Rank	#138	Overall
	#24	Key-value stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

aws.amazon.com/simpledb

cloud.google.com/bigquery

www.stardog.com

terminusdb.com

yanza.com

Technical documentation

docs.aws.amazon.com/simpledb

cloud.google.com/bigquery/docs

docs.stardog.com

terminusdb.github.io/terminusdb/#

Developer

Amazon

Google

Stardog-Union

DataChemist Ltd.

Yanza

Initial release

2007

2010

2018

2015

Current release

7.3.0, May 2020

11.0.0, January 2023

License

Commercial or Open Source

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

GPL V3

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Prolog, Rust

Server operating systems

hosted

Linux
macOS
Windows

Linux

Windows

Data scheme

schema-free

yes

schema-free and OWL/RDFS-schema support

yes

schema-free

Typing

predefined data types such as float or date

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.

Import/export of XML data possible

Secondary indexes

yes

All columns are indexed automatically

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

SQL-like query language (WOQL)

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

HTTP API

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

JavaScript
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

in JavaScript

user defined functions and aggregates, HTTP Server extensions in Java

yes

Triggers

yes

via event handlers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

none

Graph Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication in HA-Cluster

Journaling Streams

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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 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)

Access rights for users and roles

Role-based access control

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