DBMS > Apache Cassandra vs. HEAVY.AI vs. Netezza vs. Teradata

System Properties Comparison Apache Cassandra vs. HEAVY.AI vs. Netezza vs. Teradata

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Data warehouse and analytics appliance part of IBM PureSystems

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Wide column store

Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	98.94
Rank	#11	Overall
	#1	Wide column stores

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Score	41.47
Rank	#22	Overall
	#15	Relational DBMS

Website

cassandra.apache.org

github.com/heavyai/heavydb
www.heavy.ai

www.ibm.com/products/netezza

www.teradata.com

Technical documentation

cassandra.apache.org/doc/latest

docs.heavy.ai

docs.teradata.com

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

HEAVY.AI, Inc.

IBM

Teradata

Initial release

2008

2016

2000

1984

Current release

5.0-rc1, July 2024

5.10, January 2022

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2; enterprise edition available

commercial

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

C++ and CUDA

Server operating systems

BSD
Linux
OS X
Windows

Linux

included in appliance

hosted
Linux

Data scheme

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

restricted

only equality queries, not always the best performing solution

yes

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

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

yes

SQL 2016 + extensions

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
OLE DB

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

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/Thrift
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

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

Server-side scripts

Stored procedures

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

Round robin

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

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

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

Apache Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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