DBMS > Drizzle vs. Oracle Berkeley DB vs. SAP Advantage Database Server vs. SpatiaLite vs. WakandaDB

System Properties Comparison Drizzle vs. Oracle Berkeley DB vs. SAP Advantage Database Server vs. SpatiaLite vs. WakandaDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Widely used in-process key-value store

Low-cost RDBMS with access to ISAM and FoxPro data structures

Spatial extension of SQLite

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Spatial DBMS

Object oriented DBMS

Secondary database models

Relational DBMS

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

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

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

www.sap.com/products/advantage-database-server.html

www.gaia-gis.it/fossil/libspatialite/index

wakanda.github.io

Technical documentation

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

www.gaia-gis.it/gaia-sins/spatialite_topics.html

wakanda.github.io/doc

Developer

Drizzle project, originally started by Brian Aker

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Sybase, SAP

Alessandro Furieri

Wakanda SAS

Initial release

2008

1994

1993

2008

2012

Current release

7.2.4, September 2012

18.1.40, May 2020

5.0.0, August 2020

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

commercial license available

commercial

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Open Source

AGPLv3, extended commercial license available

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++

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

C++

C++, JavaScript

Server operating systems

FreeBSD
Linux
OS X

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
Windows

server-less

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

JDBC

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API

Supported programming languages

C
C++
Java
PHP

.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

Delphi
Perl
PHP

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

hooks for callbacks inside the server can be used.

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
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

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

caching of (temporary) tables can be configured

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

yes

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