DBMS > EventStoreDB vs. Faircom DB vs. HEAVY.AI vs. OpenQM

System Properties Comparison EventStoreDB vs. Faircom DB vs. HEAVY.AI vs. OpenQM

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Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

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

Primary database model

Event Store

Key-value store
Relational DBMS

Relational DBMS

Multivalue DBMS

Secondary database models

Spatial DBMS

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

Score	1.07
Rank	#181	Overall
	#1	Event Stores

Score	0.18
Rank	#314	Overall
	#45	Key-value stores
	#141	Relational DBMS

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Website

www.eventstore.com

www.faircom.com/products/faircom-db

github.com/heavyai/heavydb
www.heavy.ai

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

Technical documentation

developers.eventstore.com

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

docs.heavy.ai

Developer

Event Store Limited

FairCom Corporation

HEAVY.AI, Inc.

Rocket Software, originally Martin Phillips

Initial release

2012

1979

2016

1993

Current release

21.2, February 2021

V13, July 2024

5.10, January 2022

3.4-12

License

Commercial or Open Source

Open Source

commercial

Restricted, free version available

Open Source

Apache Version 2; enterprise edition available

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

ANSI C, C++

C++ and CUDA

Server operating systems

Linux
Windows

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

schema free, schema optional, schema required, partial schema,

yes

with some exceptions

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

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

yes, ANSI SQL with proprietary extensions

yes

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

JDBC
ODBC
Thrift
Vega

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

All languages supporting JDBC/ODBC/Thrift
Python

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

Round robin

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

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

Fine grained access rights according to SQL-standard with additional protections for files

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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