DBMS > Bangdb vs. DataFS vs. Infobright vs. Sphinx

System Properties Comparison Bangdb vs. DataFS vs. Infobright vs. Sphinx

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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.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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

Primary database model

Document store
Graph DBMS
Time Series DBMS

Object oriented DBMS

Relational DBMS

Search engine

Secondary database models

Spatial DBMS

Graph DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

bangdb.com

newdatabase.com

ignitetech.com/softwarelibrary/infobrightdb

sphinxsearch.com

Technical documentation

docs.bangdb.com

dev.mobiland.com/Overview.xsp

sphinxsearch.com/docs

Developer

Sachin Sinha, BangDB

Mobiland AG

Ignite Technologies Inc.; formerly InfoBright Inc.

Sphinx Technologies Inc.

Initial release

2012

2018

2005

2001

Current release

BangDB 2.0, October 2021

1.1.263, October 2022

3.5.1, February 2023

License

Commercial or Open Source

Open Source

BSD 3

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

GPL version 2, commercial licence available

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

Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
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)

yes

Typing

predefined data types such as float or date

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

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

secondary, composite, nested, reverse, geospatial

Knowledge Grid Technology used instead

yes

full-text index on all search fields

SQL

Support of SQL

SQL like support with command line tool

yes

SQL-like query language (SphinxQL)

APIs and other access methods

Proprietary protocol
RESTful HTTP API

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
ODBC

Proprietary protocol

Supported programming languages

C
C#
C++
Java
Python

.Net
C
C#
C++
VB.Net

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Triggers

yes, Notifications (with Streaming only)

no, except callback-events from server when changes happened

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

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

none

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

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 Sphinx index.

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

yes

User concepts

Access control

yes (enterprise version only)

Windows-Profile

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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More resources

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