DBMS > HugeGraph vs. LevelDB vs. Lovefield vs. SQLite

System Properties Comparison HugeGraph vs. LevelDB vs. Lovefield vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Embeddable relational database for web apps written in pure JavaScript

Widely used embeddable, in-process RDBMS

Primary database model

Graph DBMS

Key-value store

Relational DBMS

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

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Score	2.75
Rank	#107	Overall
	#19	Key-value stores

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

github.com/google/leveldb

google.github.io/lovefield

www.sqlite.org

Technical documentation

hugegraph.apache.org/docs

github.com/google/leveldb/blob/main/doc/index.md

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

www.sqlite.org/docs.html

Developer

Baidu

Google

Dwayne Richard Hipp

Initial release

2018

2011

2014

2000

Current release

0.9

1.23, February 2021

2.1.12, February 2017

3.45.2 (12 March 2024), March 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

Apache 2.0

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

JavaScript

Server operating systems

Linux
macOS
Unix

Illumos
Linux
OS X
Windows

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

tested with Chrome, Firefox, IE, Safari

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

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

also supports composite index and range index

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

SQL-92 is not fully supported

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Groovy
Java
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

asynchronous Gremlin script jobs

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

with automatic compression on writes

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

yes

User concepts

Access control

Users, roles and permissions

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