DBMS > Apache IoTDB vs. Derby vs. GeoMesa vs. RisingWave

System Properties Comparison Apache IoTDB vs. Derby vs. GeoMesa vs. RisingWave

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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

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Primary database model

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.64
Rank	#238	Overall
	#110	Relational DBMS

Website

iotdb.apache.org

db.apache.org/derby

www.geomesa.org

www.risingwave.com/database

Technical documentation

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

db.apache.org/derby/manuals/index.html

www.geomesa.org/documentation/stable/user/index.html

docs.risingwave.com/docs/current/intro

Developer

Apache Software Foundation

CCRi and others

RisingWave Labs

Initial release

2018

1997

2014

2022

Current release

1.1.0, April 2023

10.17.1.0, November 2023

5.0.0, May 2024

1.2, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache version 2

Open Source

Apache License 2.0

Open Source

Apache Version 2.0

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

Java

Scala

Rust

Server operating systems

All OS with a Java VM (>= 1.8)

All OS with a Java VM

Docker
Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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

APIs and other access methods

JDBC
Native API

JDBC

JDBC
PostgreSQL wire protocol

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Java Stored Procedures

UDFs in Python or Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

depending on storage layer

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

Source-replica replication

depending on storage layer

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

depending on storage layer

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 capabilities

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

yes

depending on storage layer

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

Users and Roles

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More resources

DB-Engines blog posts

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6 April 2021, Matthias Gelbmann

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