DBMS > Apache Phoenix vs. Geode vs. Microsoft Azure Table Storage

System Properties Comparison Apache Phoenix vs. Geode vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines

Name

Description

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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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

Primary database model

Relational DBMS

Key-value store

Wide column store

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

Score	1.90
Rank	#121	Overall
	#59	Relational DBMS

Score	1.45
Rank	#148	Overall
	#24	Key-value stores

Score	3.05
Rank	#84	Overall
	#6	Wide column stores

Website

phoenix.apache.org

geode.apache.org

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

Technical documentation

phoenix.apache.org

geode.apache.org/docs

Developer

Apache Software Foundation

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Microsoft

Initial release

2014

2002

2012

Current release

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

1.1, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Linux
Unix
Windows

All OS with a Java VM

the JDK (8 or later) is also required

hosted

Data scheme

yes

late-bound, schema-on-read capabilities

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (OQL)

APIs and other access methods

JDBC

Java Client API
Memcached protocol
RESTful HTTP API

RESTful HTTP API

Supported programming languages

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

.Net
All JVM based languages
C++
Groovy
Java
Scala

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

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

yes

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

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes, on a single node

optimistic locking

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

User concepts

Access control

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

Access rights per client and object definable

Access rights based on private key authentication or shared access signatures

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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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