DBMS > GeoMesa vs. Lovefield vs. SWC-DB

System Properties Comparison GeoMesa vs. Lovefield vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Embeddable relational database for web apps written in pure JavaScript

A high performance, scalable Wide Column DBMS

Primary database model

Spatial DBMS

Relational DBMS

Wide column store

Secondary database models

Time Series DBMS

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

Score	0.72
Rank	#220	Overall
	#4	Spatial DBMS

Score	0.13
Rank	#338	Overall
	#149	Relational DBMS

Score	0.01
Rank	#377	Overall
	#13	Wide column stores

Website

www.geomesa.org

google.github.io/lovefield

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

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

Developer

CCRi and others

Google

Alex Kashirin

Initial release

2014

2020

Current release

5.0.1, July 2024

2.1.12, February 2017

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

JavaScript

C++

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

Linux

Data scheme

yes

schema-free

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

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

Proprietary protocol
Thrift

Supported programming languages

JavaScript

C++

Server-side scripts

Stored procedures

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

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.

depending on storage layer

yes

using MemoryDB

User concepts

Access control

yes

depending on the DBMS used for storage

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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