DBMS > Lovefield vs. Microsoft Azure AI Search vs. Netezza vs. Postgres-XL vs. RDF4J

System Properties Comparison Lovefield vs. Microsoft Azure AI Search vs. Netezza vs. Postgres-XL vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

Search-as-a-service for web and mobile app development

Data warehouse and analytics appliance part of IBM PureSystems

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Secondary database models

Vector DBMS

Document store
Spatial DBMS

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

google.github.io/lovefield

azure.microsoft.com/en-us/services/search

www.ibm.com/products/netezza

www.postgres-xl.org

rdf4j.org

Technical documentation

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

learn.microsoft.com/en-us/azure/search

www.postgres-xl.org/documentation

rdf4j.org/documentation

Developer

Google

Microsoft

IBM

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2014

2015

2000

2014

since 2012, originally named StormDB

2004

Current release

2.1.12, February 2017

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Mozilla public license

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

JavaScript

Java

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

hosted

Linux

included in appliance

Linux
macOS

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

distributed, parallel query execution

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
OLE DB

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

JavaScript

C#
Java
JavaScript
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

yes

using Azure authentication

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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