DBMS > Manticore Search vs. Microsoft Azure Cosmos DB vs. Microsoft Azure SQL Database vs. PouchDB vs. Sadas Engine

System Properties Comparison Manticore Search vs. Microsoft Azure Cosmos DB vs. Microsoft Azure SQL Database vs. PouchDB vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

Multi-storage database for search, including full-text search.

Globally distributed, horizontally scalable, multi-model database service

Database as a Service offering with high compatibility to Microsoft SQL Server

JavaScript DBMS with an API inspired by CouchDB

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Document store

Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.29
Rank	#302	Overall
	#21	Search engines

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

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

manticoresearch.com

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/en-us/products/azure-sql/database

pouchdb.com

www.sadasengine.com

Technical documentation

manual.manticoresearch.com

learn.microsoft.com/azure/cosmos-db

docs.microsoft.com/en-us/azure/azure-sql

pouchdb.com/guides

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Manticore Software

Microsoft

Apache Software Foundation

SADAS s.r.l.

Initial release

2017

2014

2010

2012

2006

Current release

6.0, February 2023

V12

7.1.1, June 2019

8.0

License

Commercial or Open Source

Open Source

GPL version 2

commercial

Open Source

commercial

free trial version 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++

JavaScript

C++

Server operating systems

FreeBSD
Linux
macOS
Windows

hosted

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

AIX
Linux
Windows

Data scheme

Fixed schema

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

yes

All properties auto-indexed by default

yes

via views

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

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

ADO.NET
JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

JDBC
ODBC
Proprietary protocol

Supported programming languages

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

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

JavaScript

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

JavaScript

Transact SQL

View functions in JavaScript

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

Implicit feature of the cloud service

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

yes

Implicit feature of the cloud service

yes, with always 3 replicas available

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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