DBMS > Bangdb vs. Oracle Berkeley DB vs. Realm vs. SAP SQL Anywhere

System Properties Comparison Bangdb vs. Oracle Berkeley DB vs. Realm vs. SAP SQL Anywhere

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Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

Widely used in-process key-value store

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Score	7.18
Rank	#52	Overall
	#8	Document stores

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Website

bangdb.com

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

realm.io

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

docs.bangdb.com

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

realm.io/docs

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Sachin Sinha, BangDB

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Realm, acquired by MongoDB in May 2019

SAP

formerly Sybase

Initial release

2012

1994

2014

1992

Current release

BangDB 2.0, October 2021

18.1.40, May 2020

17, July 2015

License

Commercial or Open Source

Open Source

BSD 3

Open Source

commercial license available

Open Source

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

C, C++

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

Server operating systems

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Android
Backend: server-less
iOS
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

yes

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

.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
Java

with Android only
Objective-C
React Native
Swift

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

yes, in C/C++, Java, .Net or Perl

Triggers

yes, Notifications (with Streaming only)

yes

only for the SQL API

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Source-replica replication

none

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

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, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

In-Memory realm

yes

User concepts

Access control

yes (enterprise version only)

yes

fine grained access rights according to SQL-standard

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