DBMS > Atos Standard Common Repository vs. EventStoreDB vs. Kingbase vs. SwayDB vs. VictoriaMetrics

System Properties Comparison Atos Standard Common Repository vs. EventStoreDB vs. Kingbase vs. SwayDB vs. VictoriaMetrics

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.

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

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

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Document store
Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Website

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

Technical documentation

developers.eventstore.com

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Atos Convergence Creators

Event Store Limited

BeiJing KINGBASE Information technologies inc.

Simer Plaha

VictoriaMetrics

Initial release

2016

2012

1999

2018

Current release

1703

21.2, February 2021

V8.0, August 2021

v1.91, May 2023

License

Commercial or Open Source

commercial

Open Source

commercial

Open Source

GNU Affero GPL V3.0

Open Source

Apache Version 2.0

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 and Java

Scala

Server operating systems

Linux

Linux
Windows

FreeBSD
Linux
macOS
OpenBSD

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

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

Standard with numerous extensions

APIs and other access methods

LDAP

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

All languages with LDAP bindings

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Synchronous 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

Immediate Consistency

Eventual 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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