DBMS > Spark SQL vs. SpatiaLite vs. TempoIQ

System Properties Comparison Spark SQL vs. SpatiaLite vs. TempoIQ

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

Spark SQL is a component on top of 'Spark Core' for structured data processing

Spatial extension of SQLite

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Relational DBMS

Spatial DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	19.15
Rank	#33	Overall
	#20	Relational DBMS

Score	1.72
Rank	#149	Overall
	#3	Spatial DBMS

Website

spark.apache.org/sql

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

tempoiq.com (offline)

Technical documentation

spark.apache.org/docs/latest/sql-programming-guide.html

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

Developer

Apache Software Foundation

Alessandro Furieri

TempoIQ

Initial release

2014

2008

2012

Current release

3.5.0 ( 2.13), September 2023

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

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

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

C++

Server operating systems

Linux
OS X
Windows

server-less

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 DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

HTTP API

Supported programming languages

Java
Python
R
Scala

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

User concepts

Access control

simple authentication-based access control

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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