DBMS > BigObject vs. Microsoft Azure SQL Database vs. OrigoDB vs. VelocityDB

System Properties Comparison BigObject vs. Microsoft Azure SQL Database vs. OrigoDB vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Database as a Service offering with high compatibility to Microsoft SQL Server

A fully ACID in-memory object graph database

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Document store
Object oriented DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	72.95
Rank	#16	Overall
	#11	Relational DBMS

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS
	#21	Object oriented DBMS

Website

bigobject.io

azure.microsoft.com/en-us/products/azure-sql/database

origodb.com

velocitydb.com

Technical documentation

docs.bigobject.io

docs.microsoft.com/en-us/azure/azure-sql

origodb.com/docs

velocitydb.com/UserGuide

Developer

BigObject, Inc.

Microsoft

Robert Friberg et al

VelocityDB Inc

Initial release

2015

2010

2009

under the name LiveDB

2011

Current release

V12

7.x

License

Commercial or Open Source

commercial

free community edition available

commercial

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

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

hosted

Linux
Windows

Any that supports .NET

Data scheme

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

yes

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

.NET Client API
HTTP API
LINQ

.Net

Supported programming languages

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net

Server-side scripts

Stored procedures

Lua

Transact SQL

yes

Triggers

yes

Domain Events

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, with always 3 replicas available

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role based authorization

Based on Windows Authentication

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