DBMS > Atos Standard Common Repository vs. EventStoreDB vs. Heroic vs. SwayDB vs. Transwarp ArgoDB

System Properties Comparison Atos Standard Common Repository vs. EventStoreDB vs. Heroic vs. SwayDB vs. Transwarp ArgoDB

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

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Document store
Key-value store

Secondary database models

Search engine

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

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

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

Score	0.12
Rank	#348	Overall
	#151	Relational DBMS

Website

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

www.eventstore.com

github.com/spotify/heroic

swaydb.simer.au

www.transwarp.cn/en/product/argodb

Technical documentation

developers.eventstore.com

spotify.github.io/heroic

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

Atos Convergence Creators

Event Store Limited

Spotify

Simer Plaha

Transwarp

Initial release

2016

2012

2014

2018

Current release

1703

21.2, February 2021

License

Commercial or Open Source

commercial

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

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

SQL

Support of SQL

yes

APIs and other access methods

LDAP

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

Supported programming languages

All languages with LDAP bindings

Java
Kotlin
Scala

Server-side scripts

Stored procedures

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

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

Transaction concepts

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

Atomic execution of specific operations

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

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