DBMS > Amazon Redshift vs. Bangdb vs. EsgynDB vs. H2GIS

System Properties Comparison Amazon Redshift vs. Bangdb vs. EsgynDB vs. H2GIS

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Spatial extension of H2

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Spatial DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	0.15
Rank	#334	Overall
	#45	Document stores
	#31	Graph DBMS
	#31	Time Series DBMS

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	0.05
Rank	#372	Overall
	#7	Spatial DBMS

Website

aws.amazon.com/redshift

bangdb.com

www.esgyn.cn

www.h2gis.org

Technical documentation

docs.aws.amazon.com/redshift

docs.bangdb.com

www.h2gis.org/docs/home

Developer

Amazon (based on PostgreSQL)

Sachin Sinha, BangDB

Esgyn

CNRS

Initial release

2012

2015

2013

Current release

BangDB 2.0, October 2021

License

Commercial or Open Source

commercial

Open Source

BSD 3

commercial

Open Source

LGPL 3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C++, Java

Java

Server operating systems

hosted

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

restricted

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL like support with command line tool

yes

APIs and other access methods

JDBC
ODBC

Proprietary protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Java
Python

All languages supporting JDBC/ODBC/ADO.Net

Java

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

yes

based on H2

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Multi-source replication between multi datacenters

yes

based on H2

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

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

yes, run db with in-memory only mode

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes (enterprise version only)

fine grained access rights according to SQL-standard

yes

based on H2

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