DBMS > Microsoft Azure Cosmos DB vs. Quasardb vs. RavenDB vs. Sphinx

System Properties Comparison Microsoft Azure Cosmos DB vs. Quasardb vs. RavenDB vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

Distributed, high-performance timeseries database

Open Source Operational and Transactional Enterprise NoSQL Document Database

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Document store

Search engine

Secondary database models

Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.13
Rank	#332	Overall
	#28	Time Series DBMS

Score	2.68
Rank	#102	Overall
	#19	Document stores

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

azure.microsoft.com/services/cosmos-db

quasar.ai

ravendb.net

sphinxsearch.com

Technical documentation

learn.microsoft.com/azure/cosmos-db

doc.quasar.ai/master

ravendb.net/docs

sphinxsearch.com/docs

Developer

Microsoft

quasardb

Hibernating Rhinos

Sphinx Technologies Inc.

Initial release

2014

2009

2010

2001

Current release

3.14.1, January 2024

5.4, July 2022

3.5.1, February 2023

License

Commercial or Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

AGPL version 3, commercial license available

Open Source

GPL version 2, commercial licence available

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

C++

Server operating systems

hosted

BSD
Linux
OS X
Windows

Linux
macOS
Raspberry Pi
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

integer and binary

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

with tags

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

SQL-like query language (RQL)

SQL-like query language (SphinxQL)

APIs and other access methods

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

HTTP API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Proprietary protocol

Supported programming languages

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

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

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

JavaScript

yes

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

consistent hashing

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication with selectable replication factor

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

User concepts

Access control

Access rights can be defined down to the item level

Cryptographically strong user authentication and audit trail

Authorization levels configured per client per database

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