DBMS > Oracle Berkeley DB vs. Sadas Engine vs. SAP Advantage Database Server vs. Spark SQL vs. SpatiaLite

System Properties Comparison Oracle Berkeley DB vs. Sadas Engine vs. SAP Advantage Database Server vs. Spark SQL vs. SpatiaLite

Editorial information provided by DB-Engines

Name

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

Description

Widely used in-process key-value store

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Spatial extension of SQLite

Primary database model

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Spatial 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	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Website

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

www.sadasengine.com

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

spark.apache.org/sql

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

Technical documentation

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

spark.apache.org/docs/latest/sql-programming-guide.html

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

Developer

Oracle

originally developed by Sleepycat, which was acquired by Oracle

SADAS s.r.l.

Sybase, SAP

Apache Software Foundation

Alessandro Furieri

Initial release

1994

2006

1993

2014

2008

Current release

18.1.40, May 2020

8.0

3.5.0 ( 2.13), September 2023

5.0.0, August 2020

License

Commercial or Open Source

Open Source

commercial license available

commercial

free trial version available

commercial

Open Source

Apache 2.0

Open Source

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

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)

C++

Scala

C++

Server operating systems

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

AIX
Linux
Windows

Linux
Windows

Linux
OS X
Windows

server-less

Data scheme

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

SQL interfaced based on SQLite is available

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC

Supported programming languages

.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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Delphi
Perl
PHP

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

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

managed by 'Learn by Usage'

caching of (temporary) tables can be configured

yes

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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