DBMS > LMDB vs. Oracle Berkeley DB vs. SQLite

System Properties Comparison LMDB vs. Oracle Berkeley DB vs. SQLite

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

Widely used in-process key-value store

Widely used embeddable, in-process RDBMS

Primary database model

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

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

Score	1.75
Rank	#127	Overall
	#20	Key-value stores

Score	1.71
Rank	#129	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	114.09
Rank	#10	Overall
	#7	Relational DBMS

Website

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

www.oracle.com/database/technologies/related/berkeleydb.html

www.sqlite.org

Technical documentation

www.lmdb.tech/doc

docs.oracle.com/cd/E17076_05/html/index.html

www.sqlite.org/docs.html

Developer

Symas

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Dwayne Richard Hipp

Initial release

2011

1994

2000

Current release

0.9.32, January 2024

18.1.40, May 2020

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

Open Source

commercial license 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.

Implementation language

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux
Unix
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

server-less

Data scheme

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes

SQL-92 is not fully supported

APIs and other access methods

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

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

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

via file-system locks

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Big gains for Relational Database Management Systems in DB-Engines Ranking
2 February 2016, Matthias Gelbmann

show all

Recent citations in the news

Pandas Can’t Handle This: How ArcticDB Powers Massive Datasets
12 February 2025, Towards Data Science

The Lightning Memory-mapped Database
2 March 2016, infoq.com

Threat Actors Exploit Multiple Vulnerabilities in Ivanti Connect Secure and Policy Secure Gateways
29 February 2024, CISA (.gov)

Akamai launches managed database service
25 April 2022, Blocks and Files

Introducing Quicksilver: Configuration Distribution at Internet Scale
30 March 2020, The Cloudflare Blog

provided by Google News

Recognition For NoSQL Pioneers
5 July 2021, i-programmer.info

ACM recognizes far-reaching technical achievements with special awards
26 May 2021, EurekAlert!

Which Are the Top Local Databases for React Native
15 October 2019, appinventiv.com

Database Trends Report: SQL Beats NoSQL, MySQL Most Popular
5 March 2019, ADTmag

Fig. 2. XML Methods for Various XML DBMS Types
29 October 2024, ResearchGate

provided by Google News

A Coding Guide to Build an Agentic AI‑Powered Asynchronous Ticketing Assistant Using PydanticAI Agents, Pydantic v2, and SQLite Database
22 April 2025, MarkTechPost

Zero-latency SQLite storage in every Durable Object
26 September 2024, The Cloudflare Blog

Google’s AI Tool Big Sleep Finds Zero-Day Vulnerability in SQLite Database Engine
4 November 2024, The Hacker News

SQLite re-implemented in Rust to achieve asynchronous I/O and other changes
12 December 2024, devclass

How to install SQLite on Windows
20 October 2024, theserverside.com

provided by Google News

Share this page