DBMS > Apache IoTDB vs. EXASOL vs. Interbase vs. SpatiaLite

System Properties Comparison Apache IoTDB vs. EXASOL vs. Interbase vs. SpatiaLite

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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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Light-weight proven RDBMS

originally from Borland

Spatial extension of SQLite

Primary database model

Time Series DBMS

Relational DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

iotdb.apache.org

www.exasol.com

www.embarcadero.com/products/interbase

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

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

www.exasol.com/resources

docs.embarcadero.com/products/interbase

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Apache Software Foundation

Exasol

Embarcadero

Alessandro Furieri

Initial release

2018

2000

1984

2008

Current release

1.1.0, April 2023

InterBase 2020, December 2019

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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++

Server operating systems

All OS with a Java VM (>= 1.8)

Android
iOS
Linux
OS X
Windows

server-less

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.

export as XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

.Net
JDBC
ODBC
WebSocket

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java
Lua
Python
R

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

yes

Interbase procedure and trigger language

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

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

Interbase Change Views

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Hadoop integration

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

Multiversion concurreny control

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

User concepts

Access control

yes

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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