DBMS > Apache IoTDB vs. H2 vs. IBM Db2 Event Store vs. JSqlDb

System Properties Comparison Apache IoTDB vs. H2 vs. IBM Db2 Event Store vs. JSqlDb

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Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Distributed Event Store optimized for Internet of Things use cases

JavaScript Query Language Database, stores JavaScript objects and primitives

Primary database model

Time Series DBMS

Relational DBMS

Event Store
Time Series DBMS

Document store
Object oriented DBMS

Secondary database models

Spatial DBMS

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

Score	1.19
Rank	#176	Overall
	#15	Time Series DBMS

Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Score	0.23
Rank	#316	Overall
	#2	Event Stores
	#28	Time Series DBMS

Website

iotdb.apache.org

www.h2database.com

www.ibm.com/products/db2-event-store

jsqldb.org (offline)

Technical documentation

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

www.h2database.com/html/main.html

www.ibm.com/docs/en/db2-event-store

Developer

Apache Software Foundation

Thomas Mueller

IBM

Konrad von Backstrom

Initial release

2018

2005

2017

2018

Current release

1.1.0, April 2023

2.2.220, July 2023

2.0

0.8, December 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

free developer edition available

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

Server operating systems

All OS with a Java VM (>= 1.8)

All OS with a Java VM

Linux

Linux, macOS, Windows for the developer addition

Linux
macOS
Windows

Data scheme

yes

schema-free

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

SQL-like query language

yes

through the embedded Spark runtime

APIs and other access methods

JDBC
Native API

JDBC
ODBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

JavaScript

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

yes

functions in JavaScript

Triggers

yes

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

With clustering: 2 database servers on different computers operate on identical copies of a database

Active-active shard replication

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

Eventual 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)

No - written data is immutable

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

using RocksDB

In-memory capabilities

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

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

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