DBMS > Datomic vs. Sadas Engine vs. Transwarp ArgoDB vs. VelocityDB

System Properties Comparison Datomic vs. Sadas Engine vs. Transwarp ArgoDB vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Search engine

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.12
Rank	#348	Overall
	#151	Relational DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

www.datomic.com

www.sadasengine.com

www.transwarp.cn/en/product/argodb

velocitydb.com

Technical documentation

docs.datomic.com

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

velocitydb.com/UserGuide

Developer

Cognitect

SADAS s.r.l.

Transwarp

VelocityDB Inc

Initial release

2012

2006

2011

Current release

1.0.6735, June 2023

8.0

7.x

License

Commercial or Open Source

commercial

limited edition free

commercial

free trial version available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, Clojure

C++

Server operating systems

All OS with a Java VM

AIX
Linux
Windows

Any that supports .NET

Data 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

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Proprietary protocol

.Net

Supported programming languages

Clojure
Java

.Net
C
C#
C++
Groovy
Java
PHP
Python

.Net

Server-side scripts

Stored procedures

yes

Transaction Functions

Triggers

By using transaction functions

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

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

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

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

managed by 'Learn by Usage'

yes

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

Based on Windows Authentication

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