DBMS > Amazon SimpleDB vs. Google BigQuery vs. OrigoDB vs. TypeDB

System Properties Comparison Amazon SimpleDB vs. Google BigQuery vs. OrigoDB vs. TypeDB

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Editorial information provided by DB-Engines

Name

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

A fully ACID in-memory object graph database

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Key-value store

Relational DBMS

Document store
Object oriented DBMS

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

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

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.70
Rank	#230	Overall
	#20	Graph DBMS
	#106	Relational DBMS

Website

aws.amazon.com/simpledb

cloud.google.com/bigquery

origodb.com

typedb.com

Technical documentation

docs.aws.amazon.com/simpledb

cloud.google.com/bigquery/docs

origodb.com/docs

typedb.com/docs

Developer

Amazon

Google

Robert Friberg et al

Vaticle

Initial release

2007

2010

2009

under the name LiveDB

2016

Current release

2.26.3, January 2024

License

Commercial or Open Source

commercial

Open Source

GPL Version 3, commercial licenses available

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

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

All columns are indexed automatically

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

.NET Client API
HTTP API
LINQ

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

none

horizontal partitioning

client side managed; servers are not synchronized

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

depending on model

substituted by the relationship feature

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

Write ahead log

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)

Role based authorization

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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