DBMS > H2GIS vs. Heroic vs. LMDB vs. Lovefield vs. PouchDB

System Properties Comparison H2GIS vs. Heroic vs. LMDB vs. Lovefield vs. PouchDB

Editorial information provided by DB-Engines

Name

Description

Spatial extension of H2

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A high performant, light-weight, embedded key-value database library

Embeddable relational database for web apps written in pure JavaScript

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Secondary database models

Relational DBMS

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

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

www.h2gis.org

github.com/spotify/heroic

www.symas.com/symas-embedded-database-lmdb

google.github.io/lovefield

pouchdb.com

Technical documentation

www.h2gis.org/docs/home

spotify.github.io/heroic

www.lmdb.tech/doc

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

pouchdb.com/guides

Developer

CNRS

Spotify

Symas

Google

Apache Software Foundation

Initial release

2013

2014

2011

2014

2012

Current release

0.9.32, January 2024

2.1.12, February 2017

7.1.1, June 2019

License

Commercial or Open Source

Open Source

LGPL 3.0

Open Source

Apache 2.0

Open Source

Apache 2.0

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

Java

JavaScript

Server operating systems

Linux
Unix
Windows

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

tested with Chrome, Firefox, IE, Safari

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

Data scheme

yes

schema-free

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

via Elasticsearch

yes

via views

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

Java

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

JavaScript

Server-side scripts

Stored procedures

yes

based on H2

View functions in JavaScript

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

yes

none

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual 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, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

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

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

yes

based on H2

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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