DBMS > HEAVY.AI vs. IBM Db2 vs. TerminusDB

System Properties Comparison HEAVY.AI vs. IBM Db2 vs. TerminusDB

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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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

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

Graph DBMS

Secondary database models

Spatial DBMS

Document store
RDF store

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

with Db2 Spatial Extender

Document store
RDF store

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

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	127.49
Rank	#8	Overall
	#5	Relational DBMS

Score	0.22
Rank	#323	Overall
	#28	Graph DBMS

Website

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

www.ibm.com/products/db2

terminusdb.com

Technical documentation

docs.heavy.ai

www.ibm.com/docs/en/db2

terminusdb.github.io/terminusdb/#

Developer

HEAVY.AI, Inc.

IBM

DataChemist Ltd.

Initial release

2016

1983

host version

2018

Current release

5.10, January 2022

12.1, October 2016

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

free version is available

Open Source

GPL V3

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

C++ and CUDA

C and C++

Prolog, Rust

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

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

JavaScript
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

only with Windows/Unix/Linux Version

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

with separate tools (MQ, InfoSphere)

Journaling Streams

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 journaling

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

Role-based access control

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More resources

Recent citations in the news

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, businesswire.com

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14 April 2023, InfoWorld

HEAVY.AI Partners with Bain, Maxar, and Nvidia to Provide Digital Twins for Telecom Networks
16 February 2023, Datanami

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29 November 2023, The Register

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15 March 2021, Tech.eu

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