DBMS > JaguarDB vs. Lovefield vs. Netezza vs. OpenMLDB

System Properties Comparison JaguarDB vs. Lovefield vs. Netezza vs. OpenMLDB

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Editorial information provided by DB-Engines

Name

Description

Performant, highly scalable DBMS for AI and IoT applications

Embeddable relational database for web apps written in pure JavaScript

Data warehouse and analytics appliance part of IBM PureSystems

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

Primary database model

Key-value store
Vector DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	0.02
Rank	#367	Overall
	#37	Time Series DBMS

Website

www.jaguardb.com

google.github.io/lovefield

www.ibm.com/products/netezza

openmldb.ai

Technical documentation

www.jaguardb.com/support.html

github.com/google/lovefield/blob/master/docs/spec_index.md

openmldb.ai/docs/zh/main

Developer

DataJaguar, Inc.

Google

IBM

4 Paradigm Inc.

Initial release

2015

2014

2000

2020

Current release

3.3 July 2023

2.1.12, February 2017

2024-2 February 2024

License

Commercial or Open Source

Open Source

GPL V3.0

Open Source

Apache 2.0

commercial

Open Source

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++

the server part. Clients available in other languages

JavaScript

C++, Java, Scala

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux

included in appliance

Linux

Data scheme

yes

Fixed schema

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
OLE DB

JDBC
SQLAlchemy

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript

C
C++
Fortran
Java
Lua
Perl
Python
R

C++
Go
Java
Python
Scala

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

rights management via user accounts

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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More resources

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