DBMS > Atos Standard Common Repository vs. Microsoft Azure Cosmos DB vs. NSDb vs. OrigoDB vs. VictoriaMetrics

System Properties Comparison Atos Standard Common Repository vs. Microsoft Azure Cosmos DB vs. NSDb vs. OrigoDB 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

Globally distributed, horizontally scalable, multi-model database service

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A fully ACID in-memory object graph database

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

Primary database model

Document store
Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Document store
Object oriented DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Website

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

azure.microsoft.com/services/cosmos-db

nsdb.io

origodb.com

victoriametrics.com

Technical documentation

learn.microsoft.com/azure/cosmos-db

nsdb.io/Architecture

origodb.com/docs

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

Developer

Atos Convergence Creators

Microsoft

Robert Friberg et al

VictoriaMetrics

Initial release

2016

2014

2017

2009

under the name LiveDB

2018

Current release

1703

v1.91, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Java, Scala

Server operating systems

Linux

hosted

Linux
macOS

Linux
Windows

FreeBSD
Linux
macOS
OpenBSD

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

Typing

predefined data types such as float or date

optional

yes

JSON types

yes: int, bigint, decimal, string

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

All properties auto-indexed by default

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

LDAP

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

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

Supported programming languages

All languages with LDAP bindings

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Java
Scala

.Net

Server-side scripts

Stored procedures

JavaScript

yes

Triggers

yes

JavaScript

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

Atomic execution of specific operations

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

Write ahead log

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

Access rights can be defined down to the item level

Role based authorization

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