DBMS > Amazon SimpleDB vs. Google BigQuery vs. ITTIA vs. MaxDB vs. SAP SQL Anywhere

System Properties Comparison Amazon SimpleDB vs. Google BigQuery vs. ITTIA vs. MaxDB vs. SAP SQL Anywhere

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

Edge Time Series DBMS with Real-Time Stream Processing

A robust and reliable RDBMS optimized to run all major SAP solutions

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Secondary database models

Relational 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	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

aws.amazon.com/simpledb

cloud.google.com/bigquery

www.ittia.com

maxdb.sap.com

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

docs.aws.amazon.com/simpledb

cloud.google.com/bigquery/docs

maxdb.sap.com/documentation

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Amazon

Google

ITTIA L.L.C.

SAP, acquired from Software AG (Adabas-D) in 1997

SAP

formerly Sybase

Initial release

2007

2010

2007

1984

1992

Current release

8.7

7.9.10.12, February 2024

17, July 2015

License

Commercial or Open Source

commercial

Limited community edition free

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 and C++

C++

Server operating systems

hosted

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Fixed schema

yes

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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

All columns are indexed automatically

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API
WebSocket

ADO.NET
JDBC
ODBC
WebDAV

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
JavaScript (Node.js)
Python

.Net
C#
Java
Perl
PHP
Python

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Database mirroring

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

Foreign keys

Referential integrity

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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)

Database file passwords

fine grained access rights according to SQL-standard

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