DBMS > Sadas Engine vs. VelocityDB vs. VoltDB vs. YottaDB

System Properties Comparison Sadas Engine vs. VelocityDB vs. VoltDB vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

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

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

Graph DBMS
Object oriented DBMS

Relational DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

Technical documentation

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

velocitydb.com/UserGuide

docs.voltdb.com

yottadb.com/resources/documentation

Developer

SADAS s.r.l.

VelocityDB Inc

VoltDB Inc.

YottaDB, LLC

Initial release

2006

2011

2010

2001

Current release

8.0

7.x

11.3, April 2022

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Open Source

AGPL 3.0

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

C++

Java, C++

Server operating systems

AIX
Linux
Windows

Any that supports .NET

Linux
OS X

for development

Docker
Linux

Data scheme

yes

schema-free

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

only a subset of SQL 99

by using the Octo plugin

APIs and other access methods

JDBC
ODBC
Proprietary protocol

.Net

Java API
JDBC
RESTful HTTP/JSON API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

.Net

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

Java

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

yes

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

FOREIGN KEY constraints are not supported

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Transactions are executed single-threaded within stored procedures

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

yes

In-memory capabilities

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

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

Users and roles with access to stored procedures

Users and groups based on OS-security mechanisms

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More resources

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