DBMS > Apache Phoenix vs. FatDB vs. Teradata vs. VoltDB

System Properties Comparison Apache Phoenix vs. FatDB vs. Teradata vs. VoltDB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A hybrid cloud data analytics software platform (Teradata Vantage)

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Document store
Key-value store

Relational 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	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

phoenix.apache.org

www.teradata.com

www.voltdb.com

Technical documentation

phoenix.apache.org

docs.teradata.com

docs.voltdb.com

Developer

Apache Software Foundation

FatCloud

Teradata

VoltDB Inc.

Initial release

2014

2012

1984

2010

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

Teradata Vantage 1.0 MU2, January 2019

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Java, C++

Server operating systems

Linux
Unix
Windows

Windows

hosted
Linux

Linux
OS X

for development

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

yes

Typing

predefined data types such as float or date

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

Secondary indexes

yes

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

yes

SQL

Support of SQL

yes

Via inetgration in SQL Server

yes

SQL 2016 + extensions

yes

only a subset of SQL 99

APIs and other access methods

JDBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

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

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

via applications

yes

UDFs, stored procedures, table functions in parallel

Java

Triggers

yes

via applications

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

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

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

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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Bridge the SQL-NoSQL gap with Apache Phoenix
4 February 2016, InfoWorld

Hortonworks Starts Hadoop Summit with Data Platform Update -- ADTmag
28 June 2016, ADT Magazine

Deep dive into Azure HDInsight 4.0
25 September 2018, azure.microsoft.com

Amazon EMR 4.7.0 – Apache Tez & Phoenix, Updates to Existing Apps | Amazon Web Services
2 June 2016, AWS Blog

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21 May 2024, MarketBeat

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31 August 2021, PR Newswire

VoltDB Turns to Real-Time Analytics with NewSQL Database
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provided by Google News

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