DBMS > atoti vs. DataFS vs. Datomic vs. Microsoft SQL Server vs. NSDb

System Properties Comparison atoti vs. DataFS vs. Datomic vs. Microsoft SQL Server vs. NSDb

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

Microsofts flagship relational DBMS

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

Primary database model

Object oriented DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Graph DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

atoti.io

newdatabase.com

www.datomic.com

www.microsoft.com/en-us/sql-server

nsdb.io

Technical documentation

docs.atoti.io

dev.mobiland.com/Overview.xsp

docs.datomic.com

learn.microsoft.com/en-US/sql/sql-server

nsdb.io/Architecture

Developer

ActiveViam

Mobiland AG

Cognitect

Microsoft

Initial release

2018

2012

1989

2017

Current release

1.1.263, October 2022

1.0.6735, June 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

free versions available

commercial

limited edition free

commercial

restricted free version is available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, Clojure

C++

Java, Scala

Server operating systems

Windows

All OS with a Java VM

Linux
Windows

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.

yes

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

Multidimensional Expressions (MDX)

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
OLE DB
Tabular Data Stream (TDS)

gRPC
HTTP REST
WebSocket

Supported programming languages

.Net
C
C#
C++
VB.Net

Clojure
Java

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Java
Scala

Server-side scripts

Stored procedures

Python

yes

Transaction Functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

no, except callback-events from server when changes happened

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Proprietary Sharding system

none

But extensive use of caching in the application peers

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes, but depending on the SQL-Server Edition

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

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

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

yes

User concepts

Access control

Windows-Profile

fine grained access rights according to SQL-standard

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