DBMS > Apache Phoenix vs. Machbase Neo vs. mSQL vs. Postgres-XL vs. SwayDB

System Properties Comparison Apache Phoenix vs. Machbase Neo vs. mSQL vs. Postgres-XL vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

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

TimeSeries DBMS for AIoT and BigData

mSQL (Mini SQL) is a simple and lightweight RDBMS

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

phoenix.apache.org

machbase.com

hughestech.com.au/products/msql

www.postgres-xl.org

swaydb.simer.au

Technical documentation

phoenix.apache.org

machbase.com/dbms

www.postgres-xl.org/documentation

Developer

Apache Software Foundation

Machbase

Hughes Technologies

Simer Plaha

Initial release

2014

2013

1994

2014

since 2012, originally named StormDB

2018

Current release

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

V8.0, August 2023

4.4, October 2021

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free test version available

commercial

free licenses can be provided

Open Source

Mozilla public license

Open Source

GNU Affero GPL V3.0

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

Scala

Server operating systems

Linux
Unix
Windows

Linux
macOS
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
macOS

Data scheme

yes

late-bound, schema-on-read capabilities

yes

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

distributed, parallel query execution

APIs and other access methods

JDBC

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

JDBC
ODBC

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#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C
C++
Delphi
Java
Perl
PHP
Tcl

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

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

none

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

Atomic execution of operations

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.

yes

volatile and lookup table

yes

User concepts

Access control

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

simple password-based access control

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Azure #HDInsight Apache Phoenix now supports Zeppelin
16 August 2018, Microsoft

Bridge the SQL-NoSQL gap with Apache Phoenix
4 February 2016, InfoWorld

Apache Calcite, FreeMarker, Gora, Phoenix, and Solr updated
27 March 2017, SDTimes.com

Hortonworks Starts Hadoop Summit with Data Platform Update -- ADTmag
28 June 2016, ADT Magazine

provided by Google News

Higher Education PS rules out ghost students before PAC
29 November 2018, diggers.news

provided by Google News

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