DBMS > Amazon Redshift vs. Microsoft Azure Cosmos DB vs. Raima Database Manager vs. VictoriaMetrics

System Properties Comparison Amazon Redshift vs. Microsoft Azure Cosmos DB vs. Raima Database Manager vs. VictoriaMetrics

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Globally distributed, horizontally scalable, multi-model database service

RDBMS with a small footprint, either embedded into an application or used as a database server

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

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS
Time Series DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.46
Rank	#259	Overall
	#120	Relational DBMS
	#22	Time Series DBMS

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Website

aws.amazon.com/redshift

azure.microsoft.com/services/cosmos-db

raima.com

victoriametrics.com

Technical documentation

docs.aws.amazon.com/redshift

learn.microsoft.com/azure/cosmos-db

docs.raima.com

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

Developer

Amazon (based on PostgreSQL)

Microsoft

Raima Inc.

VictoriaMetrics

Initial release

2012

2014

1984

2018

Current release

15, June 2021

v1.91, May 2023

License

Commercial or Open Source

commercial

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

Server operating systems

hosted

Android
HP-UX
Integrity RTOS
iOS
Linux
OS X
QNX
Solaris
VxWorks
Windows

FreeBSD
Linux
macOS
OpenBSD

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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.

Exporting/Importing of XML structures possible

Secondary indexes

restricted

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

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

ADO.NET
JDBC
ODBC
RESTful HTTP API

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

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net
C
C++
Objective-C
PL/SQL

Server-side scripts

Stored procedures

user defined functions

in Python

JavaScript

yes

based on the ANSI/ISO SQL Persistent Stored Modules (PSM) specification

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

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

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

More information provided by the system vendor

Specific characteristics

Raima Database Manager (RDM) is an embedded time-series database optimized to run...
» more

Competitive advantages

Decreased time-to-market Industry-standard interfaces & tools for making your job...
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Typical application scenarios

Typical use cases include: Internet of Things (IoT) Embedded In-Memory Database Time-Series...
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Key customers

Infor, ABB, The Boeing Company, BAE Systems, Dow Jones, Dun & Bradstreet, Fujitsu,...
» more

Market metrics

Over 30 000 applications developers worldwide have field-tested RDM products More...
» more

Licensing and pricing models

Just as the technical aspects of Raima Database Manager are flexible, so are the...
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News

Raima Unveils RaimaDB 16.0: Elevating Database Performance and User Experience
29 February 2024

Raima Announces Release of Raima Database Manager (RDM) v15, a Powerful Embedded Time Series Database
10 June 2021

Raima Announces Release of Raima Database Manager (RDM) v14.2, a Powerful IoT Edge Embedded Database
8 October 2020

Raima Joins BlackBerry QNX Channel Partner Program to Deliver Safety-Critical and Secure Software Solutions
1 October 2020

Raima Expands Their Reseller Network in Asia
19 May 2020

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.