DBMS > Atos Standard Common Repository vs. eXtremeDB vs. GeoSpock vs. Hive vs. MySQL

System Properties Comparison Atos Standard Common Repository vs. eXtremeDB vs. GeoSpock vs. Hive vs. MySQL

Editorial information provided by DB-Engines

Name

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

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

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

Natively in-memory DBMS with options for persistency, high-availability and clustering

Spatial and temporal data processing engine for extreme data scale

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Widely used open source RDBMS

Primary database model

Document store
Key-value store

Relational DBMS
Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

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

Score	0.73
Rank	#227	Overall
	#104	Relational DBMS
	#18	Time Series DBMS

Score	62.59
Rank	#18	Overall
	#12	Relational DBMS

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Website

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

www.mcobject.com

geospock.com

hive.apache.org

www.mysql.com

Technical documentation

www.mcobject.com/docs/extremedb.htm

cwiki.apache.org/confluence/display/Hive/Home

dev.mysql.com/doc

Developer

Atos Convergence Creators

McObject

GeoSpock

Apache Software Foundation

initially developed by Facebook

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2016

2001

2012

1995

Current release

1703

8.2, 2021

2.0, September 2019

3.1.3, April 2022

8.3.0, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are 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++

Java, Javascript

Java

C and C++

Server operating systems

Linux

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

optional

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

support of XML interfaces available

yes

Secondary indexes

yes

temporal, categorical

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

ANSI SQL for query only (using Presto)

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

LDAP

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

JDBC

JDBC
ODBC
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

All languages with LDAP bindings

.Net
C
C#
C++
Java
Lua
Python
Scala

C++
Java
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

proprietary syntax

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

horizontal partitioning / sharding

Automatic sharding

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic execution of specific operations

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

table locks or row locks depending on storage engine

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

LDAP bind authentication

Access rights for users can be defined per table

Access rights for users, groups and roles

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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