DBMS > Amazon DynamoDB vs. Apache IoTDB vs. HEAVY.AI vs. IBM Db2 warehouse vs. InterSystems IRIS

System Properties Comparison Amazon DynamoDB vs. Apache IoTDB vs. HEAVY.AI vs. IBM Db2 warehouse vs. InterSystems IRIS

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

Cloud-based data warehousing service

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

Primary database model

Document store
Key-value store

Time Series DBMS

Relational DBMS

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Secondary database models

Spatial DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	4.05
Rank	#83	Overall
	#14	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#45	Relational DBMS

Website

aws.amazon.com/dynamodb

iotdb.apache.org

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

www.ibm.com/products/db2/warehouse

www.intersystems.com/products/intersystems-iris

Technical documentation

docs.aws.amazon.com/dynamodb

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

docs.heavy.ai

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

Developer

Amazon

Apache Software Foundation

HEAVY.AI, Inc.

IBM

InterSystems

Initial release

2012

2018

2016

2014

2018

Current release

1.1.0, April 2023

5.10, January 2022

2023.3, June 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

Open Source

Apache Version 2; enterprise edition 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

Java

C++ and CUDA

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

Linux

hosted

AIX
Linux
macOS
Ubuntu
Windows

Data scheme

schema-free

yes

depending on used data model

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

JDBC
Native API

JDBC
ODBC
Thrift
Vega

.NET Client API
JDBC
ODBC
OLE DB

JDBC
ODBC
RESTful HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Go
Java
Python
Scala

All languages supporting JDBC/ODBC/Thrift
Python

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

.Net
C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

PL/SQL, SQL PL

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

Round robin

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Multi-source replication

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

ACID across one or more tables within a single AWS account and region

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 and roles can be defined via the AWS Identity and Access Management (IAM)

yes

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

Specific characteristics

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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