DBMS > Apache Phoenix vs. Geode vs. Microsoft Azure Cosmos DB vs. Transbase

System Properties Comparison Apache Phoenix vs. Geode vs. Microsoft Azure Cosmos DB vs. Transbase

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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

Globally distributed, horizontally scalable, multi-model database service

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	2.02
Rank	#130	Overall
	#63	Relational DBMS

Score	1.99
Rank	#133	Overall
	#23	Key-value stores

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.15
Rank	#337	Overall
	#147	Relational DBMS

Website

phoenix.apache.org

geode.apache.org

azure.microsoft.com/services/cosmos-db

www.transaction.de/en/products/transbase.html

Technical documentation

phoenix.apache.org

geode.apache.org/docs

learn.microsoft.com/azure/cosmos-db

www.transaction.de/en/products/transbase/features.html

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

Transaction Software GmbH

Initial release

2014

2002

2014

1987

Current release

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

1.1, February 2017

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

free development license

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++

Server operating systems

Linux
Unix
Windows

All OS with a Java VM

the JDK (8 or later) is also required

hosted

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

SQL-like query language (OQL)

SQL-like query language

yes

APIs and other access methods

JDBC

Java Client API
Memcached protocol
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

JavaScript

yes

Triggers

yes

Cache Event Listeners

JavaScript

yes

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

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

Multi-item ACID transactions with snapshot isolation within a partition

yes

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 can be defined down to the item level

fine grained access rights according to SQL-standard

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