DBMS > OpenMLDB vs. OrigoDB vs. SpatiaLite vs. Vertica vs. VoltDB

System Properties Comparison OpenMLDB vs. OrigoDB vs. SpatiaLite vs. Vertica 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 fully ACID in-memory object graph database

Spatial extension of SQLite

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

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
Object oriented DBMS

Spatial DBMS

Relational DBMS

Column oriented

Relational DBMS

Secondary database models

Relational DBMS

Spatial DBMS
Time Series DBMS

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

Score	0.11
Rank	#339	Overall
	#30	Time Series DBMS

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

Score	1.56
Rank	#142	Overall
	#3	Spatial DBMS

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

openmldb.ai

origodb.com

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

www.vertica.com

www.voltdb.com

Technical documentation

openmldb.ai/docs/zh/main

origodb.com/docs

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

vertica.com/documentation

docs.voltdb.com

Developer

4 Paradigm Inc.

Robert Friberg et al

Alessandro Furieri

OpenText

previously Micro Focus and Hewlett Packard

VoltDB Inc.

Initial release

2020

2009

under the name LiveDB

2008

2005

2010

Current release

2024-2 February 2024

5.0.0, August 2020

12.0.3, January 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

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

commercial

Limited community edition free

Open Source

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

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java, Scala

C++

Java, C++

Server operating systems

Linux

Linux
Windows

server-less

Linux

Linux
OS X

for development

Data scheme

Fixed schema

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

yes

SQL

Support of SQL

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

yes

only a subset of SQL 99

APIs and other access methods

JDBC
SQLAlchemy

.NET Client API
HTTP API
LINQ

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C++
Go
Java
Python
Scala

.Net

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Java

Triggers

yes

Domain Events

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

client side managed; servers are not synchronized

none

horizontal partitioning, hierarchical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

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

User concepts

Access control

fine grained access rights according to SQL-standard

Role based authorization

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

Users and roles with access to stored procedures

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

MLOp practice: using OpenMLDB in the real-time anti-fraud model for the bank's online transaction
23 August 2021, Towards Data Science

Predictive maintenance — 5minutes demo of an end to end machine learning project
13 August 2021, Towards Data Science

Compared to Native Spark 3.0, We Have Achieved Significant Optimization Effects in the AI
3 August 2021, Towards Data Science

provided by Google News

Vertica on Kubernetes
20 June 2024, OpenText

What’s New in OpenText Vertica
10 January 2024, OpenText

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
12 March 2024, Datanami

MapR Hadoop Upgrade Spins YARN, Supports HP Vertica Analytics Platform
31 May 2024, Data Center Knowledge

Querying a Vertica data source in Amazon Athena using the Athena Federated Query SDK
11 February 2021, AWS Blog

provided by Google News

VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

Unveiling Volt Active Data’s game-changing approach to limitless app performance
16 October 2023, YourStory

VoltDB Aims for Fast Big Data Development
29 January 2015, ADT Magazine

Solutions Review Sits Down with VoltDB CEO David Flower
17 April 2018, Solutions Review

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
12 March 2024, Datanami

provided by Google News

Share this page