DBMS > Ingres vs. Kyligence Enterprise vs. PostgreSQL

System Properties Comparison Ingres vs. Kyligence Enterprise vs. PostgreSQL

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Editorial information provided by DB-Engines

Name

Description

Well established RDBMS

A distributed analytics engine for big data, built on top of Apache Kylin

Widely used open source RDBMS

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

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.

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	3.25
Rank	#80	Overall
	#43	Relational DBMS

Score	0.32
Rank	#273	Overall
	#126	Relational DBMS

Score	674.32
Rank	#4	Overall
	#4	Relational DBMS

Website

www.actian.com/databases/ingres

kyligence.io/kyligence-enterprise

www.postgresql.org

Technical documentation

docs.actian.com/ingres

www.postgresql.org/docs

Developer

Actian Corporation

Kyligence, Inc.

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

1974

originally developed at University Berkely in early 1970s

2016

1989

1989: Postgres, 1996: PostgreSQL

Current release

12.0, July 2024

16.4, August 2024

License

Commercial or Open Source

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Implementation language

Java

Server operating systems

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
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.

but tools for importing/exporting data from/to XML-files available

yes

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

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL for queries (using Apache Calcite)

yes

standard with numerous extensions

APIs and other access methods

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

JDBC
ODBC
RESTful HTTP API

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

Supported programming languages

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Ingres Star to access multiple databases simultaneously

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

Replication methods

Methods for redundantly storing data on multiple nodes

Ingres Replicator

Source-replica replication

other methods possible by using 3rd party extensions

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

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

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