DBMS > Firebase Realtime Database vs. Teradata vs. Trafodion vs. Transwarp Hippo

System Properties Comparison Firebase Realtime Database vs. Teradata vs. Trafodion vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

A hybrid cloud data analytics software platform (Teradata Vantage)

Transactional SQL-on-Hadoop DBMS

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

Primary database model

Document store

Relational DBMS

Vector DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Score	0.05
Rank	#386	Overall
	#14	Vector DBMS

Website

firebase.google.com/products/realtime-database

www.teradata.com

trafodion.apache.org

www.transwarp.cn/en/subproduct/hippo

Technical documentation

firebase.google.com/docs/database

docs.teradata.com

trafodion.apache.org/documentation.html

Developer

Google

acquired by Google 2014

Teradata

Apache Software Foundation, originally developed by HP

Initial release

2012

1984

2014

2023

Current release

Teradata Vantage 1.0 MU2, January 2019

2.3.0, February 2019

1.0, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

C++

Server operating systems

hosted

hosted
Linux

Linux

Linux
macOS

Data scheme

schema-free

yes

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.

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

yes

SQL

Support of SQL

yes

SQL 2016 + extensions

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

ADO.NET
JDBC
ODBC

RESTful HTTP API

Supported programming languages

Java
JavaScript
Objective-C

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

All languages supporting JDBC/ODBC/ADO.Net

C++
Java
Python

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

UDFs, stored procedures, table functions in parallel

Java Stored Procedures

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

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

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

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