DBMS > DataFS vs. Microsoft Azure Synapse Analytics vs. TimesTen vs. Ultipa

System Properties Comparison DataFS vs. Microsoft Azure Synapse Analytics vs. TimesTen vs. Ultipa

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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

In-Memory RDBMS compatible to Oracle

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Object oriented DBMS

Relational DBMS

Graph DBMS

Secondary database models

Graph DBMS

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

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Score	0.13
Rank	#335	Overall
	#31	Graph DBMS

Website

newdatabase.com

azure.microsoft.com/services/synapse-analytics

www.oracle.com/database/technologies/related/timesten.html

www.ultipa.com

Technical documentation

dev.mobiland.com/Overview.xsp

docs.microsoft.com/azure/synapse-analytics

docs.oracle.com/database/timesten-18.1

www.ultipa.com/document

Developer

Mobiland AG

Microsoft

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Ultipa

Initial release

2018

2016

1998

2019

Current release

1.1.263, October 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

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++

Server operating systems

Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

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

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

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
VB.Net

C#
Java
PHP

C
C++
Java
PL/SQL

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Transact SQL

PL/SQL

Triggers

no, except callback-events from server when changes happened

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

Windows-Profile

yes

fine grained access rights according to SQL-standard

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