DBMS > Microsoft Azure AI Search vs. SiteWhere vs. Snowflake vs. TimescaleDB

System Properties Comparison Microsoft Azure AI Search vs. SiteWhere vs. Snowflake vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

Search-as-a-service for web and mobile app development

M2M integration platform for persisting/querying time series data

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

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Secondary database models

Vector DBMS

Relational DBMS

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

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

azure.microsoft.com/en-us/services/search

github.com/sitewhere/sitewhere

www.snowflake.com

www.timescale.com

Technical documentation

learn.microsoft.com/en-us/azure/search

sitewhere1.sitewhere.io/index.html

docs.snowflake.net/manuals/index.html

docs.timescale.com

Developer

Microsoft

SiteWhere

Snowflake Computing Inc.

Timescale

Initial release

2015

2010

2014

2017

Current release

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

hosted

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

predefined scheme

yes

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

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data 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

SQL

Support of SQL

yes

full PostgreSQL SQL syntax

APIs and other access methods

RESTful HTTP API

HTTP REST

CLI Client
JDBC
ODBC

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

Supported programming languages

C#
Java
JavaScript
Python

JavaScript (Node.js)
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

yes

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

based on HBase

yes

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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

yes

using Azure authentication

Users with fine-grained authorization concept

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

fine grained access rights according to SQL-standard

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