DBMS > Amazon CloudSearch vs. Microsoft Azure Cosmos DB vs. Oracle Coherence vs. Postgres-XL vs. SQLite

System Properties Comparison Amazon CloudSearch vs. Microsoft Azure Cosmos DB vs. Oracle Coherence vs. Postgres-XL vs. SQLite

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

Globally distributed, horizontally scalable, multi-model database service

Oracles in-memory data grid solution

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Widely used embeddable, in-process RDBMS

Primary database model

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	1.81
Rank	#137	Overall
	#12	Search engines

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

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/cloudsearch

azure.microsoft.com/services/cosmos-db

www.oracle.com/java/coherence

www.postgres-xl.org

www.sqlite.org

Technical documentation

docs.aws.amazon.com/cloudsearch

learn.microsoft.com/azure/cosmos-db

docs.oracle.com/en/middleware/standalone/coherence

www.postgres-xl.org/documentation

www.sqlite.org/docs.html

Developer

Amazon

Microsoft

Oracle

Dwayne Richard Hipp

Initial release

2012

2014

2007

2014

since 2012, originally named StormDB

2000

Current release

14.1, August 2023

10 R1, October 2018

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

Open Source

Public Domain

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

hosted

All OS with a Java VM

Linux
macOS

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

JSON types

yes

not rigid because of 'dynamic typing' concept.

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

XML type, but no XML query functionality

Secondary indexes

yes

all search fields are automatically indexed

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

distributed, parallel query execution

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP API

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

JCache
JPA
RESTful HTTP API

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

.Net
C++
Java

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

JavaScript

user defined functions

Triggers

JavaScript

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

Implicit feature of the cloud service

yes, with selectable consistency level

none

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

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency
Immediate Consistency

Immediate 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

configurable

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

optionally

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

authentication via encrypted signatures

Access rights can be defined down to the item level

authentification to access the cache via certificates or http basic authentication

fine grained access rights according to SQL-standard

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