DBMS > Bangdb vs. Graph Engine vs. Netezza vs. Postgres-XL vs. SAP HANA

System Properties Comparison Bangdb vs. Graph Engine vs. Netezza vs. Postgres-XL vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Data warehouse and analytics appliance part of IBM PureSystems

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store
Graph DBMS
Time Series DBMS

Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial 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	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

bangdb.com

www.graphengine.io

www.ibm.com/products/netezza

www.postgres-xl.org

www.sap.com/products/hana.html

Technical documentation

docs.bangdb.com

www.graphengine.io/docs/manual

www.postgres-xl.org/documentation

help.sap.com/hana

Developer

Sachin Sinha, BangDB

Microsoft

IBM

SAP

Initial release

2012

2010

2000

2014

since 2012, originally named StormDB

2010

Current release

BangDB 2.0, October 2021

10 R1, October 2018

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

BSD 3

Open Source

MIT License

commercial

Open Source

Mozilla public license

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

.NET and C

Server operating systems

Linux

.NET

Linux

included in appliance

Linux
macOS

Appliance or cloud-service

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

distributed, parallel query execution

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

RESTful HTTP API

JDBC
ODBC
OLE DB

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

C#
C++
F#
Visual Basic

C
C++
Fortran
Java
Lua
Perl
Python
R

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

SQLScript, R

Triggers

yes, Notifications (with Streaming only)

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

horizontal partitioning

Sharding

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

yes

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

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

MVCC

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

User concepts

Access control

yes (enterprise version only)

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

yes

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