DBMS > Faircom DB vs. Faircom EDGE vs. Quasardb vs. QuestDB

System Properties Comparison Faircom DB vs. Faircom EDGE vs. Quasardb vs. QuestDB

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Editorial information provided by DB-Engines

Name

Description

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

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

Distributed, high-performance timeseries database

A high performance open source SQL database for time series data

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

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

Score	0.02
Rank	#370	Overall
	#55	Key-value stores
	#157	Relational DBMS

Score	0.13
Rank	#332	Overall
	#28	Time Series DBMS

Score	2.81
Rank	#98	Overall
	#7	Time Series DBMS

Website

www.faircom.com/products/faircom-db

www.faircom.com/products/faircom-edge

quasar.ai

questdb.io

Technical documentation

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

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

doc.quasar.ai/master

questdb.io/docs

Developer

FairCom Corporation

quasardb

QuestDB Technology Inc

Initial release

1979

2009

2014

Current release

V13, July 2024

V3, October 2020

3.14.1, January 2024

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Restricted, free version available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache 2.0

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++

Java (Zero-GC), C++, Rust

Server operating systems

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

easily portable to other OSs

Android
Linux

ARM, x86
Raspbian
Windows

BSD
Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

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

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

schema-free via InfluxDB Line Protocol

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes, ANSI Standard SQL Types

yes

integer and binary

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

with tags

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

yes

ANSI SQL queries

SQL-like query language

SQL with time-series extensions

APIs and other access methods

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

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

HTTP API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Supported programming languages

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

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

File partitioning

Customizable business rules for partitioning

Sharding

consistent hashing

horizontal partitioning (by timestamps)

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).

yes

Synchronous and asynchronous realtime replication based on transaction logs

Source-replica replication with selectable replication factor

Source-replica replication with eventual consistency

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

ACID for single-table writes

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

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

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

yes

through memory mapped files

User concepts

Access control

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

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Cryptographically strong user authentication and audit trail

More information provided by the system vendor

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4 September 2024

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22 August 2024

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16 August 2024

Write Time: a call for community writers
13 August 2024

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