DBMS > Heroic vs. Hyprcubd vs. Kinetica vs. OpenQM vs. Yanza

System Properties Comparison Heroic vs. Hyprcubd vs. Kinetica vs. OpenQM vs. Yanza

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Serverless Time Series DBMS

Fully vectorized database across both GPUs and CPUs

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

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Website

github.com/spotify/heroic

hyprcubd.com (offline)

www.kinetica.com

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

yanza.com

Technical documentation

spotify.github.io/heroic

docs.kinetica.com

Developer

Spotify

Hyprcubd, Inc.

Kinetica

Rocket Software, originally Martin Phillips

Yanza

Initial release

2014

2012

1993

2015

Current release

7.1, August 2021

3.4-12

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPLv2, extended commercial license available

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C, C++

Server operating systems

hosted

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Windows

Data scheme

schema-free

yes

with some exceptions

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

gRPC (https)

JDBC
ODBC
RESTful HTTP API

HTTP API

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

.Net
Basic
C
Java
Objective C
PHP
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

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

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

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

token access

Access rights for users and roles on table level

Access rights can be defined down to the item level

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