DBMS > eXtremeDB vs. Manticore Search vs. Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. Sphinx

System Properties Comparison eXtremeDB vs. Manticore Search vs. Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Natively in-memory DBMS with options for persistency, high-availability and clustering

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

Search-as-a-service for web and mobile app development

Globally distributed, horizontally scalable, multi-model database service

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

Primary database model

Relational DBMS
Time Series DBMS

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Search engine

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Vector DBMS

Spatial DBMS

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

Score	0.80
Rank	#214	Overall
	#99	Relational DBMS
	#18	Time Series DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	5.52
Rank	#59	Overall
	#6	Search engines

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

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

www.mcobject.com

manticoresearch.com

azure.microsoft.com/en-us/services/search

azure.microsoft.com/services/cosmos-db

sphinxsearch.com

Technical documentation

www.mcobject.com/docs/extremedb.htm

manual.manticoresearch.com

learn.microsoft.com/en-us/azure/search

learn.microsoft.com/azure/cosmos-db

sphinxsearch.com/docs

Developer

McObject

Manticore Software

Microsoft

Sphinx Technologies Inc.

Initial release

2001

2017

2015

2014

2001

Current release

8.2, 2021

6.0, February 2023

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

GPL version 2

commercial

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 and C++

C++

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

FreeBSD
Linux
macOS
Windows

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

Fixed schema

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

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.

support of XML interfaces available

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

All properties auto-indexed by default

yes

full-text index on all search fields

SQL

Support of SQL

yes

with the option: eXtremeSQL

SQL-like query language

SQL-like query language (SphinxQL)

APIs and other access methods

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

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

RESTful HTTP API

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

Proprietary protocol

Supported programming languages

.Net
C
C#
C++
Java
Lua
Python
Scala

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

C#
Java
JavaScript
Python

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

user defined functions

JavaScript

Triggers

yes

by defining events

JavaScript

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

Sharding

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

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

Synchronous replication based on Galera library

yes

Implicit feature of the cloud service

yes

Implicit feature of the cloud service

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

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

yes

isolated transactions for atomic changes and binary logging for safe writes

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

Durability

Support for making data persistent

yes

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

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

User concepts

Access control

yes

using Azure authentication

Access rights can be defined down to the item level

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.