DBMS > EDB Postgres vs. Microsoft Azure Data Explorer vs. SiteWhere vs. Transwarp StellarDB

System Properties Comparison EDB Postgres vs. Microsoft Azure Data Explorer vs. SiteWhere vs. Transwarp StellarDB

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Editorial information provided by DB-Engines

Name

Description

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

Fully managed big data interactive analytics platform

M2M integration platform for persisting/querying time series data

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Relational DBMS

column oriented

Time Series DBMS

Graph DBMS

Secondary database models

Document store
Spatial DBMS

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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

Score	1.86
Rank	#131	Overall
	#61	Relational DBMS

Score	3.28
Rank	#83	Overall
	#45	Relational DBMS

Score	0.07
Rank	#347	Overall
	#33	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS

Website

www.enterprisedb.com

azure.microsoft.com/services/data-explorer

github.com/sitewhere/sitewhere

www.transwarp.cn/en/product/stellardb

Technical documentation

www.enterprisedb.com/docs

docs.microsoft.com/en-us/azure/data-explorer

sitewhere1.sitewhere.io/index.html

Developer

EnterpriseDB

Microsoft

SiteWhere

Transwarp

Initial release

2005

2019

2010

Current release

14, December 2021

cloud service with continuous releases

License

Commercial or Open Source

commercial

BSD for PostgreSQL-components

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

Linux
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

predefined scheme

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

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

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

standard with numerous extensions

Kusto Query Language (KQL), SQL subset

SQL-like query language

APIs and other access methods

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

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

HTTP REST

OpenCypher

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Yes, possible languages: KQL, Python, R

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

by hash, list or range

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

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

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

Azure Active Directory Authentication

Users with fine-grained authorization concept

yes

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More resources

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