DBMS > Firebird vs. Heroic vs. Kyligence Enterprise vs. OpenQM

System Properties Comparison Firebird vs. Heroic vs. Kyligence Enterprise vs. OpenQM

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Editorial information provided by DB-Engines

Name

Description

Firebird is an open source RDBMS forked from Borland's InterBase

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

A distributed analytics engine for big data, built on top of Apache Kylin

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	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Website

www.firebirdsql.org

github.com/spotify/heroic

kyligence.io/kyligence-enterprise

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

Technical documentation

www.firebirdsql.org/en/reference-manuals

spotify.github.io/heroic

Developer

Firebird Foundation

Spotify

Kyligence, Inc.

Rocket Software, originally Martin Phillips

Initial release

2000

As fork of Borland's InterBase

2014

2016

1993

Current release

5.0.0, January 2024

3.4-12

License

Commercial or Open Source

Open Source

Initial Developer's Public License

Open Source

Apache 2.0

commercial

Open Source

GPLv2, extended commercial license available

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

C and C++

Java

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux

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

yes

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

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

JDBC
ODBC
RESTful HTTP API

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

PSQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

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

Features a multi-generational MVCC architecture, readers do not block writers

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

Users with fine-grained authorization concept

Access rights can be defined down to the item level

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More resources

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