DBMS > Lovefield vs. PostGIS vs. SiteWhere

System Properties Comparison Lovefield vs. PostGIS vs. SiteWhere

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

Spatial extension of PostgreSQL

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Spatial DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

google.github.io/lovefield

postgis.net

github.com/sitewhere/sitewhere

Technical documentation

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

postgis.net/documentation

sitewhere1.sitewhere.io/index.html

Developer

Google

SiteWhere

Initial release

2014

2005

2010

Current release

2.1.12, February 2017

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL v2.0

Open Source

Common Public Attribution License Version 1.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

Java

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Windows

Data scheme

yes

predefined scheme

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

HTTP REST

Supported programming languages

JavaScript

Server-side scripts

Stored procedures

user defined functions

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

based on PostgreSQL

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

based on PostgreSQL

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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 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

based on PostgreSQL

Users with fine-grained authorization concept

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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