DBMS > Fujitsu Enterprise Postgres vs. Google BigQuery vs. SQream DB vs. ToroDB

System Properties Comparison Fujitsu Enterprise Postgres vs. Google BigQuery vs. SQream DB vs. ToroDB

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Editorial information provided by DB-Engines

Name

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

Description

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

Large scale data warehouse service with append-only tables

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

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

Document store

Secondary database models

Document store
Spatial DBMS

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

Score	0.37
Rank	#278	Overall
	#128	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

www.postgresql.fastware.com

cloud.google.com/bigquery

sqream.com

github.com/torodb/server

Technical documentation

www.postgresql.fastware.com/product-manuals

cloud.google.com/bigquery/docs

docs.sqream.com

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Google

SQream Technologies

8Kdata

Initial release

2010

2017

2016

Current release

Fujitsu Enterprise Postgres 14, January 2022

2022.1.6, December 2022

License

Commercial or Open Source

commercial

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, CUDA, Haskell, Java, Scala

Java

Server operating systems

Linux
Windows

hosted

Linux

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

yes

string, integer, double, boolean, date, object_id

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP/JSON API

.Net
JDBC
ODBC

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

none

horizontal and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

fine grained access rights according to SQL-standard

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users and roles

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