DBMS > Apache Kylin vs. Google Cloud Firestore vs. Heroic vs. OpenQM

System Properties Comparison Apache Kylin vs. Google Cloud Firestore vs. Heroic vs. OpenQM

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Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

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

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

Primary database model

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Website

kylin.apache.org

firebase.google.com/products/firestore

github.com/spotify/heroic

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

Technical documentation

kylin.apache.org/docs

firebase.google.com/docs/firestore

spotify.github.io/heroic

Developer

Apache Software Foundation, originally contributed from eBay Inc

Google

Spotify

Rocket Software, originally Martin Phillips

Initial release

2015

2017

2014

1993

Current release

3.1.0, July 2020

3.4-12

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

Linux

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

schema-free

yes

with some exceptions

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

via Elasticsearch

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

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

Supported programming languages

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

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.

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Access rights can be defined down to the item level

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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