DBMS > Citus vs. Elasticsearch vs. Infobright vs. Microsoft Azure Cosmos DB

System Properties Comparison Citus vs. Elasticsearch vs. Infobright vs. Microsoft Azure Cosmos DB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Relational DBMS

Search engine

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store

Document store
Spatial DBMS
Vector DBMS

Spatial DBMS

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

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

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

Website

www.citusdata.com

www.elastic.co/elasticsearch

ignitetech.com/softwarelibrary/infobrightdb

azure.microsoft.com/services/cosmos-db

Technical documentation

docs.citusdata.com

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

learn.microsoft.com/azure/cosmos-db

Developer

Elastic

Ignite Technologies Inc.; formerly InfoBright Inc.

Microsoft

Initial release

2010

2005

2014

Current release

8.1, December 2018

8.6, January 2023

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

Elastic License

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

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

Server operating systems

Linux

All OS with a Java VM

Linux
Windows

hosted

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

specific XML type available, but no XML query functionality

Secondary indexes

yes

All search fields are automatically indexed

Knowledge Grid Technology used instead

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

standard, with numerous extensions

SQL-like query language

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

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

Supported programming languages

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

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

JavaScript

Triggers

yes

by using the 'percolation' feature

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

yes

Source-replica replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

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

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.

Memcached and Redis integration

yes

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Access rights can be defined down to the item level

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.