DBMS > Hive vs. mSQL vs. OrigoDB vs. TerminusDB

System Properties Comparison Hive vs. mSQL vs. OrigoDB vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Graph DBMS

Secondary database models

Document store
RDF store

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

hive.apache.org

hughestech.com.au/products/msql

origodb.com

terminusdb.com

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

origodb.com/docs

terminusdb.github.io/terminusdb/#

Developer

Apache Software Foundation

initially developed by Facebook

Hughes Technologies

Robert Friberg et al

DataChemist Ltd.

Initial release

2012

1994

2009

under the name LiveDB

2018

Current release

3.1.3, April 2022

4.4, October 2021

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free licenses can be provided

Open Source

GPL V3

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

Prolog, Rust

Server operating systems

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
Windows

Linux

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC
Thrift

JDBC
ODBC

.NET Client API
HTTP API
LINQ

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C++
Java
PHP
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net

JavaScript
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Foreign keys

Referential integrity

depending on model

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

Write ahead log

yes

in-memory journaling

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles

Role based authorization

Role-based access control

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