DBMS > Apache IoTDB vs. DuckDB vs. IBM Db2 warehouse vs. Lovefield

System Properties Comparison Apache IoTDB vs. DuckDB vs. IBM Db2 warehouse vs. Lovefield

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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

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Cloud-based data warehousing service

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Time Series DBMS

Relational DBMS

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

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	5.61
Rank	#60	Overall
	#34	Relational DBMS

Score	1.26
Rank	#162	Overall
	#73	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Website

iotdb.apache.org

duckdb.org

www.ibm.com/products/db2/warehouse

google.github.io/lovefield

Technical documentation

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

duckdb.org/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Apache Software Foundation

IBM

Google

Initial release

2018

2014

Current release

1.1.0, April 2023

1.0.0, June 2024

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT License

commercial

Open Source

Apache 2.0

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++

JavaScript

Server operating systems

All OS with a Java VM (>= 1.8)

server-less

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

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.

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
Native API

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

.NET Client API
JDBC
ODBC
OLE DB

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

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

JavaScript

Server-side scripts

Stored procedures

yes

PL/SQL, SQL PL

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

none

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

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

yes

fine grained access rights according to SQL-standard

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