DBMS > Amazon SimpleDB vs. Google BigQuery vs. IBM Db2 warehouse vs. TigerGraph

System Properties Comparison Amazon SimpleDB vs. Google BigQuery vs. IBM Db2 warehouse vs. TigerGraph

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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

Cloud-based data warehousing service

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Key-value store

Relational DBMS

Graph DBMS

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	1.37
Rank	#160	Overall
	#74	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

aws.amazon.com/simpledb

cloud.google.com/bigquery

www.ibm.com/products/db2/warehouse

www.tigergraph.com

Technical documentation

docs.aws.amazon.com/simpledb

cloud.google.com/bigquery/docs

docs.tigergraph.com

Developer

Amazon

Google

IBM

Initial release

2007

2010

2014

2017

License

Commercial or Open Source

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

C++

Server operating systems

hosted

Linux

Data scheme

schema-free

yes

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

SQL

Support of SQL

yes

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
OLE DB

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C++
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

PL/SQL, SQL PL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes

Relationships in graphs

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 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)

fine grained access rights according to SQL-standard

Role-based access control

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