DBMS > Apache IoTDB vs. HEAVY.AI vs. Microsoft Azure AI Search vs. Oracle vs. TerminusDB

System Properties Comparison Apache IoTDB vs. HEAVY.AI vs. Microsoft Azure AI Search vs. Oracle vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

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

Search-as-a-service for web and mobile app development

Widely used RDBMS

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

Primary database model

Secondary database models

Spatial DBMS

Vector DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Document store
RDF store

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

iotdb.apache.org

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

azure.microsoft.com/en-us/services/search

www.oracle.com/database

terminusdb.com

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

docs.heavy.ai

learn.microsoft.com/en-us/azure/search

docs.oracle.com/en/database

terminusdb.github.io/terminusdb/#

Developer

Apache Software Foundation

HEAVY.AI, Inc.

Microsoft

Oracle

DataChemist Ltd.

Initial release

2018

2016

2015

1980

2018

Current release

1.1.0, April 2023

5.10, January 2022

23c, September 2023

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++ and CUDA

C and C++

Prolog, Rust

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux

Data scheme

yes

Schemaless in JSON and XML columns

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

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

SQL-like query language (WOQL)

APIs and other access methods

JDBC
Native API

JDBC
ODBC
Thrift
Vega

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

All languages supporting JDBC/ODBC/Thrift
Python

C#
Java
JavaScript
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

JavaScript
Python

Server-side scripts

Stored procedures

yes

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

Round robin

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Multi-source replication

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

yes

fine grained access rights according to SQL-standard

yes

using Azure authentication

fine grained access rights according to SQL-standard

Role-based access control

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