DBMS > Atos Standard Common Repository vs. H2 vs. Hive vs. SpaceTime

System Properties Comparison Atos Standard Common Repository vs. H2 vs. Hive vs. SpaceTime

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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

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Document store
Key-value store

Relational DBMS

Spatial DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Website

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

www.h2database.com

hive.apache.org

www.mireo.com/spacetime

Technical documentation

www.h2database.com/html/main.html

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

Developer

Atos Convergence Creators

Thomas Mueller

Apache Software Foundation

initially developed by Facebook

Mireo

Initial release

2016

2005

2012

2020

Current release

1703

2.2.220, July 2023

3.1.3, April 2022

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache Version 2

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

C++

Server operating systems

Linux

All OS with a Java VM

Linux

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

A subset of ANSI SQL is implemented

APIs and other access methods

LDAP

JDBC
ODBC

JDBC
ODBC
Thrift

RESTful HTTP API

Supported programming languages

All languages with LDAP bindings

Java

C++
Java
PHP
Python

C#
C++
Python

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

With clustering: 2 database servers on different computers operate on identical copies of a database

selectable replication factor

Real-time block device replication (DRBD)

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

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

LDAP bind authentication

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

yes

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