DBMS > EsgynDB vs. Linter vs. Postgres-XL vs. PostgreSQL vs. SAP Adaptive Server

System Properties Comparison EsgynDB vs. Linter vs. Postgres-XL vs. PostgreSQL vs. SAP Adaptive Server

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

RDBMS for high security requirements

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

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

Primary database model

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	0.15
Rank	#325	Overall
	#145	Relational DBMS

Score	0.00
Rank	#386	Overall
	#159	Relational DBMS

Score	0.41
Rank	#261	Overall
	#122	Relational DBMS

Score	654.34
Rank	#4	Overall
	#4	Relational DBMS

Score	31.48
Rank	#25	Overall
	#17	Relational DBMS

Website

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

Technical documentation

www.postgres-xl.org/documentation

www.postgresql.org/docs

help.sap.com/docs/SAP_ASE

Developer

Esgyn

relex.ru

PostgreSQL Global Development Group

www.postgresql.org/developer

SAP, Sybase

Initial release

2015

1990

2014

since 2012, originally named StormDB

1989

1989: Postgres, 1996: PostgreSQL

1987

Current release

10 R1, October 2018

16.4, August 2024

16.0

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

C and C++

Server operating systems

Linux

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
macOS

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

Data scheme

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

XML type, but no XML query functionality

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

standard with numerous extensions

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++
Cobol
Java
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Java and Transact-SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

partitioning by range, list and (since PostgreSQL 11) by hash

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

MVCC

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.

User concepts

Access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

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