DBMS > BigObject vs. FatDB vs. Manticore Search vs. Percona Server for MongoDB

System Properties Comparison BigObject vs. FatDB vs. Manticore Search vs. Percona Server for MongoDB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Analytic DBMS for real-time computations and queries

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store
Key-value store

Search engine

Document store

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	0.52
Rank	#254	Overall
	#39	Document stores

Website

bigobject.io

manticoresearch.com

www.percona.com/mongodb/software/percona-server-for-mongodb

Technical documentation

docs.bigobject.io

manual.manticoresearch.com

docs.percona.com/percona-distribution-for-mongodb

Developer

BigObject, Inc.

FatCloud

Manticore Software

Percona

Initial release

2015

2012

2017

2015

Current release

6.0, February 2023

3.4.10-2.10, November 2017

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

GPL version 2

Open Source

GPL Version 2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Windows

FreeBSD
Linux
macOS
Windows

Linux

Data scheme

yes

schema-free

Fixed schema

schema-free

Typing

predefined data types such as float or date

yes

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

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

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like DML and DDL statements

Via inetgration in SQL Server

SQL-like query language

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

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

proprietary protocol using JSON

Supported programming languages

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

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Server-side scripts

Stored procedures

Lua

yes

via applications

user defined functions

JavaScript

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Synchronous replication based on Galera library

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

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

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

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

yes

In-memory capabilities

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

yes

via In-Memory Engine

User concepts

Access control

Can implement custom security layer via applications

Access rights for users and roles

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