DBMS > Bangdb vs. Manticore Search vs. Netezza

System Properties Comparison Bangdb vs. Manticore Search vs. Netezza

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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

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

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Document store
Graph DBMS
Time Series DBMS

Search engine

Relational DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

using the Manticore Columnar Library

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	0.22
Rank	#312	Overall
	#21	Search engines

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

bangdb.com

manticoresearch.com

www.ibm.com/products/netezza

Technical documentation

docs.bangdb.com

manual.manticoresearch.com

Developer

Sachin Sinha, BangDB

Manticore Software

IBM

Initial release

2012

2017

2000

Current release

BangDB 2.0, October 2021

6.0, February 2023

License

Commercial or Open Source

Open Source

BSD 3

Open Source

GPL version 2

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C++

Server operating systems

Linux

FreeBSD
Linux
macOS
Windows

Linux

included in appliance

Data scheme

schema-free

Fixed schema

yes

Typing

predefined data types such as float or date

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

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

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

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

JDBC
ODBC
OLE DB

Supported programming languages

C
C#
C++
Java
Python

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

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes, Notifications (with Streaming only)

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

Sharding

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

Sharding

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

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Foreign keys

Referential integrity

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)

Users with fine-grained authorization concept

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More resources

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