DBMS > Fujitsu Enterprise Postgres vs. H2 vs. LevelDB vs. Lovefield vs. SQLite

System Properties Comparison Fujitsu Enterprise Postgres vs. H2 vs. LevelDB vs. Lovefield vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.postgresql.fastware.com

www.h2database.com

github.com/google/leveldb

google.github.io/lovefield

www.sqlite.org

Technical documentation

www.postgresql.fastware.com/product-manuals

www.h2database.com/html/main.html

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

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Thomas Mueller

Google

Dwayne Richard Hipp

Initial release

2005

2011

2014

2000

Current release

Fujitsu Enterprise Postgres 14, January 2022

2.2.220, July 2023

1.23, February 2021

2.1.12, February 2017

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

JavaScript

Server operating systems

Linux
Windows

All OS with a Java VM

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

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

SQL-92 is not fully supported

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java

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

user defined functions

Java Stored Procedures and User-Defined Functions

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

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, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
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Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
» more

Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
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Licensing and pricing models

Core based licensing
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