DBMS > OpenMLDB vs. Oracle NoSQL vs. OrigoDB vs. SpatiaLite vs. VoltDB

System Properties Comparison OpenMLDB vs. Oracle NoSQL vs. OrigoDB vs. SpatiaLite vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

An open-source machine learning database that provides a feature platform for training and inference

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A fully ACID in-memory object graph database

Spatial extension of SQLite

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

Primary database model

Time Series DBMS

Document store
Key-value store
Relational DBMS

Document store
Object oriented DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.10
Rank	#359	Overall
	#36	Time Series DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

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

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

openmldb.ai

www.oracle.com/database/nosql/technologies/nosql

origodb.com

www.gaia-gis.it/fossil/libspatialite/index

www.voltdb.com

Technical documentation

openmldb.ai/docs/zh/main

docs.oracle.com/en/database/other-databases/nosql-database/index.html

origodb.com/docs

www.gaia-gis.it/gaia-sins/spatialite_topics.html

docs.voltdb.com

Developer

4 Paradigm Inc.

Oracle

Robert Friberg et al

Alessandro Furieri

VoltDB Inc.

Initial release

2020

2011

2009

under the name LiveDB

2008

2010

Current release

2024-2 February 2024

24.1, May 2024

5.0.0, August 2020

11.3, April 2022

License

Commercial or Open Source

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Open Source

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

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, Scala

Java

C++

Java, C++

Server operating systems

Linux

Linux
Solaris SPARC/x86

Linux
Windows

server-less

Linux
OS X

for development

Data scheme

Fixed schema

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

optional

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 DML and DDL statements

yes

only a subset of SQL 99

APIs and other access methods

JDBC
SQLAlchemy

RESTful HTTP API

.NET Client API
HTTP API
LINQ

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C++
Go
Java
Python
Scala

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

horizontal partitioning

client side managed; servers are not synchronized

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

depending on model

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Write ahead log

yes

Snapshots and command logging

In-memory capabilities

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

yes

off heap cache

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

Role based authorization

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

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