DBMS > Firebird vs. Hive vs. MySQL vs. SwayDB vs. TimescaleDB

System Properties Comparison Firebird vs. Hive vs. MySQL vs. SwayDB vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Widely used open source RDBMS

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

Key/Value like access via memcached API

Key-value store

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

Technical documentation

www.firebirdsql.org/en/reference-manuals

cwiki.apache.org/confluence/display/Hive/Home

dev.mysql.com/doc

docs.timescale.com

Developer

Firebird Foundation

Apache Software Foundation

initially developed by Facebook

Oracle

since 2010, originally MySQL AB, then Sun

Simer Plaha

Timescale

Initial release

2000

As fork of Borland's InterBase

2012

1995

2018

2017

Current release

5.0.0, January 2024

3.1.3, April 2022

8.4.0, April 2024

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Initial Developer's Public License

Open Source

Apache Version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GNU Affero GPL V3.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

C and C++

Java

C and C++

Scala

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

full PostgreSQL SQL syntax

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
ODBC
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C++
Java
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java
Kotlin
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

PSQL

yes

user defined functions and integration of map-reduce

yes

proprietary syntax

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

Multi-source replication
Source-replica replication

none

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

Atomic execution of operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

yes

table locks or row locks depending on storage engine

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.

yes

User concepts

Access control

Users with fine-grained authorization concept

Access rights for users, groups and roles

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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