DBMS > DataFS vs. Microsoft Azure Synapse Analytics vs. SiteWhere vs. TerminusDB

System Properties Comparison DataFS vs. Microsoft Azure Synapse Analytics vs. SiteWhere vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

M2M integration platform for persisting/querying time series data

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

Graph DBMS

Document store
RDF store

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

Score	0.09
Rank	#360	Overall
	#18	Object oriented DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

newdatabase.com

azure.microsoft.com/services/synapse-analytics

github.com/sitewhere/sitewhere

terminusdb.com

Technical documentation

dev.mobiland.com/Overview.xsp

docs.microsoft.com/azure/synapse-analytics

sitewhere1.sitewhere.io/index.html

terminusdb.github.io/terminusdb/#

Developer

Mobiland AG

Microsoft

SiteWhere

DataChemist Ltd.

Initial release

2018

2016

2010

2018

Current release

1.1.263, October 2022

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

Open Source

GPL V3

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++

Java

Prolog, Rust

Server operating systems

Windows

hosted

Linux
OS X
Windows

Linux

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

predefined scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (WOQL)

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
ODBC

HTTP REST

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

.Net
C
C#
C++
VB.Net

C#
Java
PHP

JavaScript
Python

Server-side scripts

Stored procedures

Transact SQL

yes

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding, horizontal partitioning

Sharding

based on HBase

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on HBase

Journaling Streams

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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 journaling

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Windows-Profile

yes

Users with fine-grained authorization concept

Role-based access control

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