DBMS > Apache Phoenix vs. Microsoft Azure Table Storage vs. Oracle vs. SingleStore

System Properties Comparison Apache Phoenix vs. Microsoft Azure Table Storage vs. Oracle vs. SingleStore

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Editorial information provided by DB-Engines

Name

Description

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

A Wide Column Store for rapid development using massive semi-structured datasets

Widely used RDBMS

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	2.02
Rank	#130	Overall
	#63	Relational DBMS

Score	4.92
Rank	#73	Overall
	#6	Wide column stores

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Score	5.91
Rank	#61	Overall
	#34	Relational DBMS

Website

phoenix.apache.org

azure.microsoft.com/en-us/services/storage/tables

www.oracle.com/database

www.singlestore.com

Technical documentation

phoenix.apache.org

docs.oracle.com/en/database

docs.singlestore.com

Developer

Apache Software Foundation

Microsoft

Oracle

SingleStore Inc.

Initial release

2014

2012

1980

2013

Current release

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

23c, September 2023

8.5, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

restricted free version is available

commercial

free developer edition available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C++, Go

Server operating systems

Linux
Unix
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux

64 bit version required

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

yes

Schemaless in JSON and XML columns

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

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

but no triggers and foreign keys

APIs and other access methods

JDBC

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

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

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication
Source-replica replication

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

can be realized in PL/SQL

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

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

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

Fine grained access control via users, groups and roles

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

F ree Tier and Enterprise Edition
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