DBMS > Apache Phoenix vs. Graph Engine vs. Linter vs. Oracle Coherence vs. PostgreSQL

System Properties Comparison Apache Phoenix vs. Graph Engine vs. Linter vs. Oracle Coherence vs. PostgreSQL

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

RDBMS for high security requirements

Oracles in-memory data grid solution

Widely used open source RDBMS

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

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Key-value store

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

Spatial DBMS

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	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Website

phoenix.apache.org

www.graphengine.io

linter.ru

www.oracle.com/java/coherence

www.postgresql.org

Technical documentation

phoenix.apache.org

www.graphengine.io/docs/manual

docs.oracle.com/en/middleware/standalone/coherence

www.postgresql.org/docs

Developer

Apache Software Foundation

Microsoft

relex.ru

Oracle

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2014

2010

1990

2007

1989

1989: Postgres, 1996: PostgreSQL

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

14.1, August 2023

16.3, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT License

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Implementation language

Java

.NET and C

C and C++

Java

Server operating systems

Linux
Unix
Windows

.NET

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

All OS with a Java VM

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

Data scheme

yes

late-bound, schema-on-read capabilities

yes

schema-free

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

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

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

APIs and other access methods

JDBC

RESTful HTTP API

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

JCache
JPA
RESTful HTTP API

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

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

C#
C++
F#
Visual Basic

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

.Net
C++
Java

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

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.

Triggers

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

yes, with selectable consistency level

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

optionally

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

fine grained access rights according to SQL-standard

More information provided by the system vendor

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