DBMS > Bangdb vs. GeoMesa vs. Microsoft Azure AI Search vs. Netezza

System Properties Comparison Bangdb vs. GeoMesa vs. Microsoft Azure AI 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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Document store
Graph DBMS
Time Series DBMS

Spatial DBMS

Search engine

Relational DBMS

Secondary database models

Spatial DBMS

Vector 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	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Website

bangdb.com

www.geomesa.org

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

www.ibm.com/products/netezza

Technical documentation

docs.bangdb.com

www.geomesa.org/documentation/stable/user/index.html

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

Developer

Sachin Sinha, BangDB

CCRi and others

Microsoft

IBM

Initial release

2012

2014

2015

2000

Current release

BangDB 2.0, October 2021

5.0.0, May 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache License 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C, C++

Scala

Server operating systems

Linux

hosted

Linux

included in appliance

Data scheme

schema-free

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

yes

SQL

Support of SQL

SQL like support with command line tool

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

RESTful HTTP API

JDBC
ODBC
OLE DB

Supported programming languages

C
C#
C++
Java
Python

C#
Java
JavaScript
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

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

depending on storage layer

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

depending on storage layer

yes

Implicit feature of the cloud service

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

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

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

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

depending on storage layer

User concepts

Access control

yes (enterprise version only)

yes

depending on the DBMS used for storage

yes

using Azure authentication

Users with fine-grained authorization concept

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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