DBMS > 4D vs. HarperDB vs. LevelDB vs. Oracle Berkeley DB vs. TimesTen

System Properties Comparison 4D vs. HarperDB vs. LevelDB vs. Oracle Berkeley DB vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

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

Widely used in-process key-value store

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Document store

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	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

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

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.4d.com

www.harperdb.io

github.com/google/leveldb

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

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

Technical documentation

developer.4d.com

docs.harperdb.io/docs

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

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

docs.oracle.com/database/timesten-18.1

Developer

4D, Inc

HarperDB

Google

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

1984

2017

2011

1994

1998

Current release

v20, April 2023

3.1, August 2021

1.23, February 2021

18.1.40, May 2020

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free community edition available

Open Source

BSD

Open Source

commercial license available

commercial

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

Node.js

C++

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

Server operating systems

OS X
Windows

Linux
OS X

Illumos
Linux
OS X
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON data types

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL-like data manipulation statements

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

4D proprietary IDE
PHP

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

Custom Functions

since release 3.1

PL/SQL

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

A table resides as a whole on one (or more) nodes in a cluster

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

the nodes on which a table resides can be defined

none

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

with automatic compression on writes

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

Users and groups

Access rights for users and roles

fine grained access rights according to SQL-standard

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