DBMS > FatDB vs. Google BigQuery vs. Infobright vs. SAP SQL Anywhere vs. SQream DB

System Properties Comparison FatDB vs. Google BigQuery vs. Infobright vs. SAP SQL Anywhere vs. SQream DB

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Large scale data warehouse service with append-only tables

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Document store
Key-value store

Relational DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

cloud.google.com/bigquery

ignitetech.com/softwarelibrary/infobrightdb

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

sqream.com

Technical documentation

cloud.google.com/bigquery/docs

help.sap.com/docs/SAP_SQL_Anywhere

docs.sqream.com

Developer

FatCloud

Google

Ignite Technologies Inc.; formerly InfoBright Inc.

SAP

formerly Sybase

SQream Technologies

Initial release

2012

2010

2005

1992

2017

Current release

17, July 2015

2022.1.6, December 2022

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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++, CUDA, Haskell, Java, Scala

Server operating systems

Windows

hosted

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

Via inetgration in SQL Server

yes

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

via applications

user defined functions

in JavaScript

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

user defined functions in Python

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

Database mirroring

none

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

Can implement custom security layer via applications

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

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

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