DBMS > Atos Standard Common Repository vs. Interbase vs. PouchDB vs. SAP Adaptive Server vs. SQLite

System Properties Comparison Atos Standard Common Repository vs. Interbase vs. PouchDB vs. SAP Adaptive Server vs. SQLite

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

Light-weight proven RDBMS

originally from Borland

JavaScript DBMS with an API inspired by CouchDB

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

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

www.embarcadero.com/products/interbase

pouchdb.com

www.sap.com/products/technology-platform/sybase-ase.html

www.sqlite.org

Technical documentation

docs.embarcadero.com/products/interbase

pouchdb.com/guides

help.sap.com/docs/SAP_ASE

www.sqlite.org/docs.html

Developer

Atos Convergence Creators

Embarcadero

Apache Software Foundation

SAP, Sybase

Dwayne Richard Hipp

Initial release

2016

1984

2012

1987

2000

Current release

1703

InterBase 2020, December 2019

7.1.1, June 2019

16.0

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

commercial

Open Source

Public Domain

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

JavaScript

C and C++

Server operating systems

Linux

Android
iOS
Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

AIX
HP-UX
Linux
Solaris
Unix
Windows

server-less

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

optional

yes

not rigid because of 'dynamic typing' concept.

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

export as XML data possible

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

APIs and other access methods

LDAP

ADO.NET
JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

All languages with LDAP bindings

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

JavaScript

C
C++
Cobol
Java
Java
Perl
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Interbase procedure and trigger language

View functions in JavaScript

Java and Transact-SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Interbase Change Views

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

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

Multiversion concurreny control

yes

via file-system locks

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

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

yes

User concepts

Access control

LDAP bind authentication

fine grained access rights according to SQL-standard

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