DBMS > Atos Standard Common Repository vs. Derby vs. Heroic vs. SwayDB vs. Valentina Server

System Properties Comparison Atos Standard Common Repository vs. Derby vs. Heroic vs. SwayDB vs. Valentina Server

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.

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Object-relational database and reports server

Primary database model

Document store
Key-value store

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

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

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

db.apache.org/derby

github.com/spotify/heroic

swaydb.simer.au

www.valentina-db.net

Technical documentation

db.apache.org/derby/manuals/index.html

spotify.github.io/heroic

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Atos Convergence Creators

Apache Software Foundation

Spotify

Simer Plaha

Paradigma Software

Initial release

2016

1997

2014

2018

1999

Current release

1703

10.17.1.0, November 2023

5.7.5

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

GNU Affero GPL V3.0

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

Server operating systems

Linux

All OS with a Java VM

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

yes

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

SQL

Support of SQL

yes

APIs and other access methods

LDAP

JDBC

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

ODBC

Supported programming languages

All languages with LDAP bindings

Java

Java
Kotlin
Scala

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

none

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

Immediate Consistency

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

Atomic execution of operations

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

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