DBMS > Faircom DB vs. Firebird vs. Hawkular Metrics vs. KairosDB vs. Microsoft Azure Synapse Analytics

System Properties Comparison Faircom DB vs. Firebird vs. Hawkular Metrics vs. KairosDB vs. Microsoft Azure Synapse Analytics

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.

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Distributed Time Series DBMS based on Cassandra or H2

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Website

www.faircom.com/products/faircom-db

www.firebirdsql.org

www.hawkular.org

github.com/kairosdb/kairosdb

azure.microsoft.com/services/synapse-analytics

Technical documentation

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

www.firebirdsql.org/en/reference-manuals

www.hawkular.org/hawkular-metrics/docs/user-guide

kairosdb.github.io

docs.microsoft.com/azure/synapse-analytics

Developer

FairCom Corporation

Firebird Foundation

Community supported by Red Hat

Microsoft

Initial release

1979

2000

As fork of Borland's InterBase

2014

2013

2016

Current release

V12, November 2020

5.0.0, January 2024

1.2.2, November 2018

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Initial Developer's Public License

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

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

ANSI C, C++

C and C++

Java

C++

Server operating systems

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

easily portable to other OSs

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
OS X
Windows

hosted

Data scheme

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

yes

schema-free

yes

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.

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

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

HTTP REST

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
ODBC

Supported programming languages

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

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

Go
Java
Python
Ruby

Java
JavaScript

Node.js
PHP
Python

C#
Java
PHP

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

PSQL

Transact SQL

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Sharding

based on Cassandra

Sharding

based on Cassandra

Sharding, horizontal partitioning

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).

Source-replica replication

selectable replication factor

based on Cassandra

selectable replication factor

based on Cassandra

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

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

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

Users with fine-grained authorization concept

simple password-based access control

yes

More information provided by the system vendor

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