DBMS > Google BigQuery vs. SAP IQ vs. SiteWhere vs. Snowflake

System Properties Comparison Google BigQuery vs. SAP IQ vs. SiteWhere vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Columnar RDBMS optimized for Big Data analytics

M2M integration platform for persisting/querying time series data

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

column-oriented

Time Series DBMS

Relational DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

cloud.google.com/bigquery

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

github.com/sitewhere/sitewhere

www.snowflake.com

Technical documentation

cloud.google.com/bigquery/docs

help.sap.com/docs/SAP_IQ

sitewhere1.sitewhere.io/index.html

docs.snowflake.net/manuals/index.html

Developer

Google

SAP, formerly Sybase

SiteWhere

Snowflake Computing Inc.

Initial release

2010

1994

2010

2014

Current release

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

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

Java

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

hosted

Data scheme

yes

predefined scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

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

ADO.NET
JDBC
ODBC
RESTful HTTP API

HTTP REST

CLI Client
JDBC
ODBC

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Java
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

shared disk or shared nothing architectures with SAP IQ Multiplexer

Sharding

based on HBase

yes

Replication methods

Methods for redundantly storing data on multiple nodes

SAP/Sybase Replication Server

selectable replication factor

based on HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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.

User concepts

Access control

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

Users with fine-grained authorization concept

Users with fine-grained authorization concept, user roles and pluggable authentication

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