DBMS > Google BigQuery vs. Percona Server for MongoDB vs. SAP IQ vs. SAP SQL Anywhere vs. Tibero

System Properties Comparison Google BigQuery vs. Percona Server for MongoDB vs. SAP IQ vs. SAP SQL Anywhere vs. Tibero

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Columnar RDBMS optimized for Big Data analytics

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

A secure RDBMS, designed for easy portability from Oracle

Primary database model

column-oriented

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Score	58.10
Rank	#19	Overall
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Score	0.60
Rank	#246	Overall
	#39	Document stores

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Website

cloud.google.com/bigquery

www.percona.com/mongodb/software/percona-server-for-mongodb

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

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

us.tmaxsoft.com/products/tibero

Technical documentation

cloud.google.com/bigquery/docs

docs.percona.com/percona-distribution-for-mongodb

help.sap.com/docs/SAP_IQ

help.sap.com/docs/SAP_SQL_Anywhere

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Google

Percona

SAP, formerly Sybase

SAP

formerly Sybase

TmaxSoft

Initial release

2010

2015

1994

1992

2003

Current release

3.4.10-2.10, November 2017

16.1 SPS04, April 2019

17, July 2015

6, April 2015

License

Commercial or Open Source

commercial

Open Source

GPL Version 2

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++

C and Assembler

Server operating systems

hosted

Linux

AIX
HP-UX
Linux
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

proprietary protocol using JSON

ADO.NET
JDBC
ODBC
RESTful HTTP API

ADO.NET
HTTP API
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

C
C#
C++
Java
Perl
PHP
Python
Ruby

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

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

in JavaScript

JavaScript

yes

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

Persistent Stored Procedure (PSM)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

none

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

SAP/Sybase Replication Server

Source-replica replication

Database mirroring

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

via In-Memory Engine

yes

planned for next version

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

Access rights for users and roles

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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