DBMS > Bangdb vs. Datomic vs. Netezza

System Properties Comparison Bangdb vs. Datomic 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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Website

bangdb.com

www.datomic.com

www.ibm.com/products/netezza

Technical documentation

docs.bangdb.com

docs.datomic.com

Developer

Sachin Sinha, BangDB

Cognitect

IBM

Initial release

2012

2000

Current release

BangDB 2.0, October 2021

1.0.7180, July 2024

License

Commercial or Open Source

Open Source

BSD 3

commercial

limited edition free

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++

Java, Clojure

Server operating systems

Linux

All OS with a Java VM

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

Clojure
Java

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Triggers

yes, Notifications (with Streaming only)

By using transaction functions

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

none

But extensive use of caching in the application peers

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

But extensive use of caching in the application peers

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

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

yes

recommended only for testing and development

User concepts

Access control

yes (enterprise version only)

Users with fine-grained authorization concept

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