DBMS > DataFS vs. Datomic vs. Microsoft Azure Synapse Analytics vs. NSDb vs. Ultipa

System Properties Comparison DataFS vs. Datomic vs. Microsoft Azure Synapse Analytics vs. NSDb vs. Ultipa

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.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Secondary database models

Graph DBMS

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

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.11
Rank	#338	Overall
	#32	Graph DBMS

Website

newdatabase.com

www.datomic.com

azure.microsoft.com/services/synapse-analytics

nsdb.io

www.ultipa.com

Technical documentation

dev.mobiland.com/Overview.xsp

docs.datomic.com

docs.microsoft.com/azure/synapse-analytics

nsdb.io/Architecture

www.ultipa.com/document

Developer

Mobiland AG

Cognitect

Microsoft

Ultipa

Initial release

2018

2012

2016

2017

2019

Current release

1.1.263, October 2022

1.0.7180, July 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

Apache Version 2.0

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, Clojure

C++

Java, Scala

Server operating systems

Windows

All OS with a Java VM

hosted

Linux
macOS

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

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

RESTful HTTP API

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
VB.Net

Clojure
Java

C#
Java
PHP

Java
Scala

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

Server-side scripts

Stored procedures

yes

Transaction Functions

Transact SQL

Triggers

no, except callback-events from server when changes happened

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

none

But extensive use of caching in the application peers

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

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

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

Using Apache Lucene

In-memory capabilities

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

yes

recommended only for testing and development

User concepts

Access control

Windows-Profile

yes

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