DBMS > OrigoDB vs. Splice Machine vs. TerminusDB vs. VelocityDB

System Properties Comparison OrigoDB vs. Splice Machine vs. TerminusDB vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

A fully ACID in-memory object graph database

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

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

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

Primary database model

Document store
Object oriented DBMS

Relational DBMS

Graph DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Document store
RDF store

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

Score	0.03
Rank	#378	Overall
	#51	Document stores
	#18	Object oriented DBMS

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

Score	0.22
Rank	#323	Overall
	#28	Graph DBMS

Score	0.11
Rank	#347	Overall
	#35	Graph DBMS
	#15	Object oriented DBMS

Website

Technical documentation

origodb.com/docs

splicemachine.com/how-it-works

terminusdb.github.io/terminusdb/#

velocitydb.com/UserGuide

Developer

Robert Friberg et al

Splice Machine

DataChemist Ltd.

VelocityDB Inc

Initial release

2009

under the name LiveDB

2014

2018

2011

Current release

3.1, March 2021

11.0.0, January 2023

7.x

License

Commercial or Open Source

Open Source

AGPL 3.0, commercial license available

Open Source

GPL V3

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

Prolog, Rust

Server operating systems

Linux
Windows

Linux
OS X
Solaris
Windows

Linux

Any that supports .NET

Data scheme

yes

Typing

predefined data types such as float or date

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

yes

SQL-like query language (WOQL)

APIs and other access methods

.NET Client API
HTTP API
LINQ

JDBC
Native Spark Datasource
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

.Net

Supported programming languages

.Net

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

JavaScript
Python

.Net

Server-side scripts

Stored procedures

yes

Java

yes

Triggers

yes

Domain Events

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

client side managed; servers are not synchronized

Shared Nothhing Auto-Sharding, Columnar Partitioning

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

in-memory journaling

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

Role based authorization

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

Role-based access control

Based on Windows Authentication

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