DBMS > Bangdb vs. DataFS vs. Manticore Search vs. PostGIS

System Properties Comparison Bangdb vs. DataFS vs. Manticore Search vs. PostGIS

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Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

Spatial extension of PostgreSQL

Primary database model

Document store
Graph DBMS
Time Series DBMS

Object oriented DBMS

Search engine

Spatial DBMS

Secondary database models

Spatial DBMS

Graph DBMS

Time Series DBMS

using the Manticore Columnar Library

Relational DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Website

Technical documentation

docs.bangdb.com

dev.mobiland.com/Overview.xsp

manual.manticoresearch.com

postgis.net/documentation

Developer

Sachin Sinha, BangDB

Mobiland AG

Manticore Software

Initial release

2012

2018

2017

2005

Current release

BangDB 2.0, October 2021

1.1.263, October 2022

6.0, February 2023

3.4.2, February 2024

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

GPL version 2

Open Source

GPL v2.0

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, C++

C++

Server operating systems

Linux

Windows

FreeBSD
Linux
macOS
Windows

Data scheme

schema-free

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

Fixed schema

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

yes

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

.NET Client API
Proprietary client DLL
WinRT client

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

Supported programming languages

C
C#
C++
Java
Python

.Net
C
C#
C++
VB.Net

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

Server-side scripts

Stored procedures

user defined functions

Triggers

yes, Notifications (with Streaming only)

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Proprietary Sharding system

Sharding

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

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Synchronous replication based on Galera library

yes

based on PostgreSQL

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate 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

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

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, run db with in-memory only mode

User concepts

Access control

yes (enterprise version only)

Windows-Profile

yes

based on PostgreSQL

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More resources

DB-Engines blog posts

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