DBMS > GridDB vs. Lovefield vs. Neo4j vs. PouchDB vs. SQLite

System Properties Comparison GridDB vs. Lovefield vs. Neo4j vs. PouchDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Scalable in-memory time series database optimized for IoT and Big Data

Embeddable relational database for web apps written in pure JavaScript

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

JavaScript DBMS with an API inspired by CouchDB

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Key-value store
Relational DBMS

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

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	44.46
Rank	#23	Overall
	#1	Graph DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

griddb.net

google.github.io/lovefield

neo4j.com

pouchdb.com

www.sqlite.org

Technical documentation

docs.griddb.net

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

neo4j.com/docs

pouchdb.com/guides

www.sqlite.org/docs.html

Developer

Toshiba Corporation

Google

Neo4j, Inc.

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2013

2014

2007

2012

2000

Current release

5.1, August 2022

2.1.12, February 2017

5.19, April 2024

7.1.1, June 2019

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

Apache 2.0

Open Source

GPL version3, commercial licenses available

Open Source

Public Domain

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.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

C++

JavaScript

Java, Scala

JavaScript

Server operating systems

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

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

server-less

Data scheme

yes

schema-free and schema-optional

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

not rigid because of 'dynamic typing' concept.

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

pluggable indexing subsystem, by default Apache Lucene

yes

via views

yes

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like query language

via JavaScript builder pattern

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

JavaScript

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

User defined Procedures and Functions

View functions in JavaScript

Triggers

yes

Using read-only observers

yes

via event handler

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes using Neo4j Fabric

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Causal Clustering using Raft protocol

available in in Enterprise Version only

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID at container level

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

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

Access rights for users can be defined per database

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Neo4j delivers graph technology that has been battle tested for performance and scale...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Neo4j is the market leader, graph database category creator, and the most widely...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Real-Time Recommendations Master Data Management Identity and Access Management Network...
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more

Market metrics

GitHub trending repository
» more

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more

News

Creating the GQL Database Language Standard
7 May 2024

This Week in Neo4j: GraphRAG, Knowledge Graphs, Open Source AI, GraphQL and more
4 May 2024

This Week in Neo4j: Nodes 2024, Data Modelling, Events, Knowledge Graphs and more
27 April 2024

GQL is Here: Your Cypher Queries in a GQL World
26 April 2024

GQL: The ISO Standard for Graphs Has Arrived
25 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.