DBMS > HEAVY.AI vs. IBM Db2 vs. Snowflake vs. Teradata vs. Tibero

System Properties Comparison HEAVY.AI vs. IBM Db2 vs. Snowflake vs. Teradata vs. Tibero

Editorial information provided by DB-Engines

Name

Description

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

Common in IBM host environments, 2 different versions for host and Windows/Linux

Cloud-based data warehousing service for structured and semi-structured data

A hybrid cloud data analytics software platform (Teradata Vantage)

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Secondary database models

Spatial DBMS

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	125.90
Rank	#9	Overall
	#6	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Website

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

www.ibm.com/products/db2

www.snowflake.com

www.teradata.com

us.tmaxsoft.com/products/tibero

Technical documentation

docs.heavy.ai

www.ibm.com/docs/en/db2

docs.snowflake.net/manuals/index.html

docs.teradata.com

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

HEAVY.AI, Inc.

IBM

Snowflake Computing Inc.

Teradata

TmaxSoft

Initial release

2016

1983

host version

2014

1984

2003

Current release

5.10, January 2022

12.1, October 2016

Teradata Vantage 1.0 MU2, January 2019

6, April 2015

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

free version is available

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++ and CUDA

C and C++

C and Assembler

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows
z/OS

hosted

hosted
Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

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

SQL 2016 + extensions

yes

APIs and other access methods

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

CLI Client
JDBC
ODBC

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

JavaScript (Node.js)
Python

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

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

user defined functions

yes

UDFs, stored procedures, table functions in parallel

Persistent Stored Procedure (PSM)

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

only with Windows/Unix/Linux Version

yes

Sharding

Hashing

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

with separate tools (MQ, InfoSphere)

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

planned for next version

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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