DBMS > Apache Phoenix vs. Atos Standard Common Repository vs. GeoMesa vs. InfinityDB

System Properties Comparison Apache Phoenix vs. Atos Standard Common Repository vs. GeoMesa vs. InfinityDB

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Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

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

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

A Java embedded Key-Value Store which extends the Java Map interface

Primary database model

Relational DBMS

Document store
Key-value store

Spatial DBMS

Key-value store

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Website

phoenix.apache.org

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.geomesa.org

boilerbay.com

Technical documentation

phoenix.apache.org

www.geomesa.org/documentation/stable/user/index.html

boilerbay.com/infinitydb/manual

Developer

Apache Software Foundation

Atos Convergence Creators

CCRi and others

Boiler Bay Inc.

Initial release

2014

2016

2014

2002

Current release

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

1703

5.0.0, May 2024

4.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache License 2.0

commercial

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

Java

Server operating systems

Linux
Unix
Windows

Linux

All OS with a Java VM

Data scheme

yes

late-bound, schema-on-read capabilities

Schema and schema-less with LDAP views

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

Typing

predefined data types such as float or date

yes

optional

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

yes

APIs and other access methods

JDBC

LDAP

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Supported programming languages

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

All languages with LDAP bindings

Java

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

depending on storage layer

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

depending on storage layer

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 or Eventual Consistency depending on configuration

depending on storage layer

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

depending on storage layer

User concepts

Access control

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

LDAP bind authentication

yes

depending on the DBMS used for storage

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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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Spatial database management systems
6 April 2021, Matthias Gelbmann

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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

Infographic: What makes a Mobile Operator's setup future proof?
10 February 2024, Atos

provided by Google News

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