DBMS > Apache IoTDB vs. Kinetica vs. Riak TS vs. Spark SQL

System Properties Comparison Apache IoTDB vs. Kinetica vs. Riak TS vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

A lightweight IoT native database management system deployable on the device and syncing the collected data with the cloud and integrated with Hadoop and Spark

Fully vectorized database across both GPUs and CPUs

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

Primary database model

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

Score	0.42
Rank	#253	Overall
	#20	Time Series DBMS

Score	0.66
Rank	#212	Overall
	#103	Relational DBMS

Score	0.25
Rank	#281	Overall
	#24	Time Series DBMS

Score	22.86
Rank	#35	Overall
	#21	Relational DBMS

Website

iotdb.apache.org

www.kinetica.com

riak.com/products/riak-ts

spark.apache.org/sql

Technical documentation

www.kinetica.com/docs

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

Developer

Apache Software Foundation

Kinetica

Basho Technologies

Apache Software Foundation

Initial release

2018

2012

2015

2014

Current release

7.1, August 2021

3.2.0, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

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, C++

Erlang

Scala

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

Linux
OS X

Linux
OS X
Windows

Data scheme

yes

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

yes

restricted

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

JDBC

JDBC
ODBC
RESTful HTTP API

HTTP API
Native Erlang Interface

JDBC
ODBC

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

user defined functions

JavaScript and Erlang

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

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 with synchronizing with the cloud

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

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

GPU vRAM or System RAM

User concepts

Access control

Access rights for users and roles on table level

More information provided by the system vendor

Specific characteristics

Native and fully vectorized database across both GPUs and CPUs, with memory first...
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Competitive advantages

Best in class geospatial and temporal analytics. Lockless architecture provides real-time...
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Typical application scenarios

Any application requiring (1) real time insights, (2) time series analysis (3) geospatial...
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Key customers

Citibank, US Air Force, Softbank, OVO, Telkomsel, USPS, 2 of the top 3 US Telcos,...
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Market metrics

The largest IoT deployment in the world, NORAD, runs on Kinetica.
» more

Licensing and pricing models

Always Free Tier in the Cloud, Pay-As-You-Go Consumption Based Pricing, and Portable...
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