DBMS > Riak TS vs. Spark SQL vs. SpatiaLite vs. Transbase

System Properties Comparison Riak TS vs. Spark SQL vs. SpatiaLite vs. Transbase

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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

Spatial extension of SQLite

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Relational DBMS

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

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

spark.apache.org/sql

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

www.transaction.de/en/products/transbase.html

Technical documentation

www.tiot.jp/riak-docs/riak/ts/latest

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

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

www.transaction.de/en/products/transbase/features.html

Developer

Open Source, formerly Basho Technologies

Apache Software Foundation

Alessandro Furieri

Transaction Software GmbH

Initial release

2015

2014

2008

1987

Current release

3.0.0, September 2022

3.5.0 ( 2.13), September 2023

5.0.0, August 2020

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

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

commercial

free development license

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

Erlang

Scala

C++

C and C++

Server operating systems

Linux
OS X

Linux
OS X
Windows

server-less

FreeBSD
Linux
macOS
Solaris
Windows

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes, limited

SQL-like DML and DDL statements

yes

APIs and other access methods

HTTP API
Native Erlang Interface

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Java
Python
R
Scala

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

Erlang

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

yes

Transaction concepts

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

ACID

yes

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

NoSQL pioneer Basho stamps its mark on time stamp data with Riak TS
6 October 2015, The Register

Basho open-sources its Riak TS database for the Internet Of Things
5 May 2016, TechCrunch

Enterprise NoSQL Database for the IoT Becomes Open Source
11 May 2016, ENGINEERING.com

Basho brings open source Riak TS database for IoT
7 May 2016, Open Source For You

Best open source databases for IoT applications
26 May 2017, Open Source For You

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Performant IPv4 Range Spark Joins | by Jean-Claude Cote
24 January 2024, Towards Data Science

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

provided by Google News

Share this page