DBMS > HEAVY.AI vs. Microsoft Azure Cosmos DB vs. OrigoDB vs. RDFox vs. UniData,UniVerse

System Properties Comparison HEAVY.AI vs. Microsoft Azure Cosmos DB vs. OrigoDB vs. RDFox vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Globally distributed, horizontally scalable, multi-model database service

A fully ACID in-memory object graph database

High performance knowledge graph and semantic reasoning engine

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Document store
Object oriented DBMS

Graph DBMS
RDF store

Multivalue DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	2.85
Rank	#98	Overall
	#1	Multivalue DBMS

Website

github.com/heavyai/heavydb
www.heavy.ai

azure.microsoft.com/services/cosmos-db

origodb.com

www.oxfordsemantic.tech

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

docs.heavy.ai

learn.microsoft.com/azure/cosmos-db

origodb.com/docs

docs.oxfordsemantic.tech

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

HEAVY.AI, Inc.

Microsoft

Robert Friberg et al

Oxford Semantic Technologies

Rocket Software

Initial release

2016

2014

2009

under the name LiveDB

2017

1985

Current release

5.10, January 2022

6.0, Septermber 2022

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise 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++ and CUDA

C++

Server operating systems

Linux

hosted

Linux
Windows

Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

yes

RDF schemas

schema-free

Typing

predefined data types such as float or date

yes

JSON types

User defined using .NET types and collections

yes

optional

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.

can be achieved using .NET

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
Thrift
Vega

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

.NET Client API
HTTP API
LINQ

RESTful HTTP API
SPARQL 1.1

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net

C
Java

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

JavaScript

yes

Triggers

JavaScript

yes

Domain Events

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

Implicit feature of the cloud service

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Implicit feature of the cloud service

Source-replica replication

replication via a shared file system

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

configurable

Concurrency

Support for concurrent manipulation of data

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

Access rights can be defined down to the item level

Role based authorization

Roles, resources, and access types

Access rights according to SQL-standard and operating system based

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