DBMS > LevelDB vs. MaxDB vs. PouchDB vs. Sequoiadb vs. SQLite

System Properties Comparison LevelDB vs. MaxDB vs. PouchDB vs. Sequoiadb vs. SQLite

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

A robust and reliable RDBMS optimized to run all major SAP solutions

JavaScript DBMS with an API inspired by CouchDB

NewSQL database with distributed OLTP and SQL

Widely used embeddable, in-process RDBMS

Primary database model

Key-value store

Relational DBMS

Document store

Document store
Relational DBMS

Relational DBMS

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

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

github.com/google/leveldb

Technical documentation

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

maxdb.sap.com/documentation

pouchdb.com/guides

www.sequoiadb.com/en/index.php?m=Files&a=index

www.sqlite.org/docs.html

Developer

Google

SAP, acquired from Software AG (Adabas-D) in 1997

Apache Software Foundation

Sequoiadb Ltd.

Dwayne Richard Hipp

Initial release

2011

1984

2012

2013

2000

Current release

1.23, February 2021

7.9.10.12, February 2024

7.1.1, June 2019

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

BSD

commercial

Limited community edition free

Open Source

Server: AGPL; Client: Apache V2

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++

JavaScript

C++

Server operating systems

Illumos
Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows

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

Linux

server-less

Data scheme

schema-free

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

via views

yes

SQL

Support of SQL

yes

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

ADO.NET
JDBC
ODBC
WebDAV

HTTP REST

only for PouchDB Server
JavaScript API

proprietary protocol using JSON

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C#
Java
Perl
PHP
Python

JavaScript

.Net
C++
Java
PHP
Python

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

View functions in JavaScript

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication

none

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

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, 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

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

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