DBMS > Faircom DB vs. Microsoft Azure AI Search vs. MongoDB vs. Sphinx vs. Warp 10

System Properties Comparison Faircom DB vs. Microsoft Azure AI Search vs. MongoDB vs. Sphinx vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Key-value store
Relational DBMS

Secondary database models

Vector DBMS

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

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

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

www.faircom.com/products/faircom-db

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

www.mongodb.com

sphinxsearch.com

www.warp10.io

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

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

www.mongodb.com/docs/manual

sphinxsearch.com/docs

www.warp10.io/content/02_Getting_started

Developer

FairCom Corporation

Microsoft

MongoDB, Inc

Sphinx Technologies Inc.

SenX

Initial release

1979

2015

2009

2001

2015

Current release

V12, November 2020

6.0.7, June 2023

3.5.1, February 2023

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

GPL version 2, commercial licence available

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

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Implementation language

ANSI C, C++

C++

Java

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

hosted

Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema free, schema optional, schema required, partial schema,

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

yes

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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.

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

Read-only SQL queries via the MongoDB Atlas SQL Interface

SQL-like query language (SphinxQL)

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Proprietary protocol

HTTP API
Jupyter
WebSocket

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

C#
Java
JavaScript
Python

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

JavaScript

yes

WarpScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

Implicit feature of the cloud service

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Sharding

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

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

yes

Implicit feature of the cloud service

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

tunable from ACID to Eventually Consistent

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

yes

optional, enabled by default

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

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

Fine grained access rights according to SQL-standard with additional protections for files

yes

using Azure authentication

Access rights for users and roles

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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