DBMS > Microsoft Azure Cosmos DB vs. Oracle vs. PouchDB vs. Sphinx vs. VictoriaMetrics

System Properties Comparison Microsoft Azure Cosmos DB vs. Oracle vs. PouchDB vs. Sphinx vs. VictoriaMetrics

Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

Widely used RDBMS

JavaScript DBMS with an API inspired by CouchDB

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

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

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

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

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Website

azure.microsoft.com/services/cosmos-db

www.oracle.com/database

pouchdb.com

sphinxsearch.com

victoriametrics.com

Technical documentation

learn.microsoft.com/azure/cosmos-db

docs.oracle.com/en/database

pouchdb.com/guides

sphinxsearch.com/docs

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

Developer

Microsoft

Oracle

Apache Software Foundation

Sphinx Technologies Inc.

VictoriaMetrics

Initial release

2014

1980

2012

2001

2018

Current release

23c, September 2023

7.1.1, June 2019

3.5.1, February 2023

v1.91, May 2023

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

GPL version 2, commercial licence available

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

C and C++

JavaScript

C++

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

server-less, requires a JavaScript environment (browser, Node.js)

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

FreeBSD
Linux
macOS
OpenBSD

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

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.

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

via views

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

SQL-like query language (SphinxQL)

APIs and other access methods

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP REST

only for PouchDB Server
JavaScript API

Proprietary protocol

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

Supported programming languages

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

JavaScript

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

JavaScript

PL/SQL

also stored procedures in Java possible

View functions in JavaScript

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

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

Multi-source replication
Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

can be realized in PL/SQL

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

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

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

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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