DBMS > Apache Phoenix vs. Linter vs. Oracle Coherence vs. PouchDB vs. Sadas Engine

System Properties Comparison Apache Phoenix vs. Linter vs. Oracle Coherence vs. PouchDB vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

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

RDBMS for high security requirements

Oracles in-memory data grid solution

JavaScript DBMS with an API inspired by CouchDB

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Secondary database models

Spatial DBMS

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

Score	1.90
Rank	#125	Overall
	#59	Relational DBMS

Score	0.03
Rank	#368	Overall
	#156	Relational DBMS

Score	1.90
Rank	#127	Overall
	#21	Key-value stores

Score	2.18
Rank	#114	Overall
	#21	Document stores

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

phoenix.apache.org

linter.ru

www.oracle.com/java/coherence

pouchdb.com

www.sadasengine.com

Technical documentation

phoenix.apache.org

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

pouchdb.com/guides

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Apache Software Foundation

relex.ru

Oracle

Apache Software Foundation

SADAS s.r.l.

Initial release

2014

1990

2007

2012

2006

Current release

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

14.1, August 2023

7.1.1, June 2019

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

commercial

free trial version available

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 and C++

Java

JavaScript

C++

Server operating systems

Linux
Unix
Windows

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

All OS with a Java VM

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

AIX
Linux
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.

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC

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

JCache
JPA
RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

JDBC
ODBC
Proprietary protocol

Supported programming languages

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

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

.Net
C++
Java

JavaScript

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax with the possibility to convert from PL/SQL

View functions in JavaScript

Triggers

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

yes, with selectable consistency level

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

managed by 'Learn by Usage'

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

Access rights for users, groups and roles according to SQL-standard

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