DBMS > Amazon Redshift vs. Firebase Realtime Database vs. Hypertable vs. Transwarp Hippo

System Properties Comparison Amazon Redshift vs. Firebase Realtime Database vs. Hypertable vs. Transwarp Hippo

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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

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

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

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.05
Rank	#386	Overall
	#16	Vector DBMS

Website

aws.amazon.com/redshift

firebase.google.com/products/realtime-database

www.transwarp.cn/en/subproduct/hippo

Technical documentation

docs.aws.amazon.com/redshift

firebase.google.com/docs/database

Developer

Amazon (based on PostgreSQL)

Google

acquired by Google 2014

Hypertable Inc.

Initial release

2012

2009

2023

Current release

0.9.8.11, March 2016

1.0, May 2023

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

commercial

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++

Server operating systems

hosted

Linux
OS X
Windows

an inofficial Windows port is available

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

restricted

only exact value or prefix value scans

SQL

Support of SQL

yes

does not fully support an SQL-standard

APIs and other access methods

JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

C++ API
Thrift

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Java
JavaScript
Objective-C

C++
Java
Perl
PHP
Python
Ruby

C++
Java
Python

Server-side scripts

Stored procedures

user defined functions

in Python

limited functionality with using 'rules'

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor on file system level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

Role based access control and fine grained access rights

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