DBMS > Atos Standard Common Repository vs. Bangdb vs. Oracle Berkeley DB vs. SQream DB

System Properties Comparison Atos Standard Common Repository vs. Bangdb vs. Oracle Berkeley DB vs. SQream DB

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Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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

Widely used in-process key-value store

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Document store
Key-value store

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

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

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

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

bangdb.com

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

sqream.com

Technical documentation

docs.bangdb.com

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

docs.sqream.com

Developer

Atos Convergence Creators

Sachin Sinha, BangDB

Oracle

originally developed by Sleepycat, which was acquired by Oracle

SQream Technologies

Initial release

2016

2012

1994

2017

Current release

1703

BangDB 2.0, October 2021

18.1.40, May 2020

2022.1.6, December 2022

License

Commercial or Open Source

commercial

Open Source

BSD 3

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

Java

C, C++

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

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

Typing

predefined data types such as float or date

optional

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

yes, ANSI Standard SQL Types

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

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

LDAP

Proprietary protocol
RESTful HTTP API

.Net
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

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

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions in Python

Triggers

yes

yes, Notifications (with Streaming only)

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

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

none

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

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 or Eventual Consistency depending on configuration

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

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

yes, run db with in-memory only mode

yes

User concepts

Access control

LDAP bind authentication

yes (enterprise version only)

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