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

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

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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.

Primary database model

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Spatial DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

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

Website

Technical documentation

github.com/AlaSQL/alasql

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

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

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

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

CCRi and others

Initial release

2014

2018

1997

2014

Current release

1.1.0, April 2023

10.17.1.0, November 2023

5.0.0, May 2024

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2.0

Open Source

Apache version 2

Open Source

Apache License 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

JavaScript

Java

Scala

Server operating systems

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

All OS with a Java VM (>= 1.8)

All OS with a Java VM

Data scheme

schema-free

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

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL-like query language

yes

APIs and other access methods

JavaScript API

JDBC
Native API

JDBC

Supported programming languages

JavaScript

C
C#
C++
Go
Java
Python
Scala

Java

Server-side scripts

Stored procedures

yes

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

none

depending on storage layer

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

none

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

yes

only for local storage and DOM-storage

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

User concepts

Access control

yes

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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