DBMS > Apache IoTDB vs. Kinetica vs. SpaceTime vs. SQream DB

System Properties Comparison Apache IoTDB vs. Kinetica vs. SpaceTime vs. SQream DB

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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

Fully vectorized database across both GPUs and CPUs

SpaceTime is a spatio-temporal DBMS with a focus on performance.

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Relational DBMS

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

Score	1.19
Rank	#176	Overall
	#15	Time Series DBMS

Score	0.69
Rank	#234	Overall
	#107	Relational DBMS

Score	0.00
Rank	#396	Overall
	#8	Spatial DBMS

Score	0.73
Rank	#228	Overall
	#105	Relational DBMS

Website

iotdb.apache.org

www.kinetica.com

www.mireo.com/spacetime

sqream.com

Technical documentation

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

docs.kinetica.com

docs.sqream.com

Developer

Apache Software Foundation

Kinetica

Mireo

SQream Technologies

Initial release

2018

2012

2020

2017

Current release

1.1.0, April 2023

7.1, August 2021

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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

C, C++

C++

C++, CUDA, Haskell, Java, Scala

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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 query language

SQL-like DML and DDL statements

A subset of ANSI SQL is implemented

yes

APIs and other access methods

JDBC
Native API

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

.Net
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C++
Java
JavaScript (Node.js)
Python

C#
C++
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

user defined functions in Python

Triggers

yes

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

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Fixed-grid hypercubes

horizontal and vertical partitioning

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

Real-time block device replication (DRBD)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency or Eventual Consistency depending on configuration

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

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

yes

Access rights for users and roles on table level

yes

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