DBMS > LevelDB vs. Lovefield vs. OrientDB

System Properties Comparison LevelDB vs. Lovefield vs. OrientDB

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Editorial information provided by DB-Engines

Name

Description

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

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store

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

Score	3.04
Rank	#112	Overall
	#21	Key-value stores

Score	0.59
Rank	#277	Overall
	#125	Relational DBMS

Score	4.33
Rank	#87	Overall
	#14	Document stores
	#4	Graph DBMS
	#12	Key-value stores

Website

github.com/google/leveldb

google.github.io/lovefield

orientdb.org

Technical documentation

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

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

www.orientdb.com/docs/last/index.html

Developer

Google

OrientDB LTD; CallidusCloud; SAP

Initial release

2011

2014

2010

Current release

1.23, February 2021

2.1.12, February 2017

3.2.17, March 2023

License

Commercial or Open Source

Open Source

BSD

Open Source

Apache 2.0

Open Source

Apache version 2

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

C++

JavaScript

Java

Server operating systems

Illumos
Linux
OS X
Windows

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

tested with Chrome, Firefox, IE, Safari

All OS with a Java JDK (>= JDK 6)

Data scheme

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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, no joins

APIs and other access methods

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

JavaScript

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

Java, Javascript

Triggers

Using read-only observers

Hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

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

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

User concepts

Access control

Access rights for users and roles; record level security configurable

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