DBMS > Atos Standard Common Repository vs. Heroic vs. HyperSQL vs. Infobright

System Properties Comparison Atos Standard Common Repository vs. Heroic vs. HyperSQL vs. Infobright

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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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Primary database model

Document store
Key-value store

Time Series DBMS

Relational DBMS

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

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	3.14
Rank	#85	Overall
	#46	Relational DBMS

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Website

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

github.com/spotify/heroic

hsqldb.org

ignitetech.com/softwarelibrary/infobrightdb

Technical documentation

spotify.github.io/heroic

hsqldb.org/web/hsqlDocsFrame.html

Developer

Atos Convergence Creators

Spotify

Ignite Technologies Inc.; formerly InfoBright Inc.

Initial release

2016

2014

2001

2005

Current release

1703

2.7.2, June 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

based on BSD license

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

Server operating systems

Linux

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

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

via Elasticsearch

yes

Knowledge Grid Technology used instead

SQL

Support of SQL

yes

APIs and other access methods

LDAP

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

All languages supporting JDBC/ODBC
Java

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate 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

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

exploiting MySQL or PostgreSQL frontend capabilities

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More resources

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provided by Google News

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