DBMS > Apache IoTDB vs. OpenQM vs. VelocityDB vs. Warp 10

System Properties Comparison Apache IoTDB vs. OpenQM vs. VelocityDB vs. Warp 10

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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

QpenQM is a high-performance, self-tuning, multi-value DBMS

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Time Series DBMS

Multivalue DBMS

Graph DBMS
Object oriented DBMS

Time Series DBMS

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

Score	1.19
Rank	#176	Overall
	#15	Time Series DBMS

Score	0.33
Rank	#286	Overall
	#10	Multivalue DBMS

Score	0.11
Rank	#347	Overall
	#35	Graph DBMS
	#15	Object oriented DBMS

Score	0.08
Rank	#358	Overall
	#35	Time Series DBMS

Website

iotdb.apache.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

velocitydb.com

www.warp10.io

Technical documentation

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

velocitydb.com/UserGuide

www.warp10.io/content/02_Getting_started

Developer

Apache Software Foundation

Rocket Software, originally Martin Phillips

VelocityDB Inc

SenX

Initial release

2018

1993

2011

2015

Current release

1.1.0, April 2023

3.4-12

7.x

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GPLv2, extended commercial license available

commercial

Open Source

Apache License 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

Server operating systems

All OS with a Java VM (>= 1.8)

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Any that supports .NET

Linux
OS X
Windows

Data scheme

yes

with some exceptions

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

JDBC
Native API

.Net

HTTP API
Jupyter
WebSocket

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

.Net

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

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

yes

Sharding

based on HBase

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

yes

selectable replication factor

based on HBase

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

based on HBase

Foreign keys

Referential integrity

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

yes

Access rights can be defined down to the item level

Based on Windows Authentication

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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