DBMS > Amazon Redshift vs. Bangdb vs. Firebase Realtime Database vs. GigaSpaces vs. Hypertable

System Properties Comparison Amazon Redshift vs. Bangdb vs. Firebase Realtime Database vs. GigaSpaces vs. Hypertable

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

An open source BigTable implementation based on distributed file systems such as Hadoop

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Document store

Document store
Object oriented DBMS

Values are user defined objects

Wide column store

Secondary database models

Spatial DBMS

Graph DBMS
Search engine

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Website

aws.amazon.com/redshift

bangdb.com

firebase.google.com/products/realtime-database

www.gigaspaces.com

Technical documentation

docs.aws.amazon.com/redshift

docs.bangdb.com

firebase.google.com/docs/database

docs.gigaspaces.com/latest/landing.html

Developer

Amazon (based on PostgreSQL)

Sachin Sinha, BangDB

Google

acquired by Google 2014

Gigaspaces Technologies

Hypertable Inc.

Initial release

2012

2000

2009

Current release

BangDB 2.0, October 2021

15.5, September 2020

0.9.8.11, March 2016

License

Commercial or Open Source

commercial

Open Source

BSD 3

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

GNU version 3. Commercial license available

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++

Java, C++, .Net

C++

Server operating systems

hosted

Linux

hosted

Linux
macOS
Solaris
Windows

Linux
OS X
Windows

an inofficial Windows port is available

Data scheme

yes

schema-free

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.

XML can be used for describing objects metadata

Secondary indexes

restricted

yes

secondary, composite, nested, reverse, geospatial

yes

restricted

only exact value or prefix value scans

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL like support with command line tool

SQL-99 for query and DML statements

APIs and other access methods

JDBC
ODBC

Proprietary protocol
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

C++ API
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Java
Python

Java
JavaScript
Objective-C

.Net
C++
Java
Python
Scala

C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

limited functionality with using 'rules'

yes

Triggers

yes, Notifications (with Streaming only)

Callbacks are triggered when data changes

yes, event driven architecture

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

selectable replication factor on file system level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

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)

yes, based on authentication and database rules

Role-based access control

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