DBMS > Apache IoTDB vs. Derby vs. Faircom EDGE vs. GeoMesa vs. LokiJS

System Properties Comparison Apache IoTDB vs. Derby vs. Faircom EDGE vs. GeoMesa vs. LokiJS

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.

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

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

In-memory JavaScript DBMS

Primary database model

Time Series DBMS

Relational DBMS

Key-value store
Relational DBMS

Spatial DBMS

Document store

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Website

iotdb.apache.org

db.apache.org/derby

www.faircom.com/products/faircom-edge

www.geomesa.org

github.com/techfort/LokiJS

Technical documentation

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

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

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

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

techfort.github.io/LokiJS

Developer

Apache Software Foundation

FairCom Corporation

CCRi and others

Initial release

2018

1997

1979

2014

Current release

1.1.0, April 2023

10.17.1.0, November 2023

V3, October 2020

5.0.0, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache version 2

commercial

Restricted, free version available

Open Source

Apache License 2.0

Open Source

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

ANSI C, C++

Scala

JavaScript

Server operating systems

All OS with a Java VM (>= 1.8)

All OS with a Java VM

Android
Linux

ARM, x86
Raspbian
Windows

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

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

via views

SQL

Support of SQL

SQL-like query language

yes

ANSI SQL queries

APIs and other access methods

JDBC
Native API

JDBC

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

JavaScript API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

JavaScript

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes

.Net, JavaScript, C/C++

View 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

File partitioning

Customizable business rules for partitioning

depending on storage layer

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

Source-replica replication

yes

Synchronous and asynchronous realtime replication based on transaction logs

depending on storage layer

none

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

Immediate Consistency
Tunable Consistency

depending on storage layer

none

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

atomic operations within a single collection possible

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

yes

depending on the DBMS used for storage

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