DBMS > Firebird vs. Microsoft SQL Server vs. Oracle vs. Splice Machine vs. Trino

System Properties Comparison Firebird vs. Microsoft SQL Server vs. Oracle vs. Splice Machine vs. Trino

Editorial information provided by DB-Engines

Name

Description

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

Microsofts flagship relational DBMS

Widely used RDBMS

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	19.46
Rank	#30	Overall
	#18	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	1286.59
Rank	#1	Overall
	#1	Relational DBMS

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Score	5.28
Rank	#61	Overall
	#35	Relational DBMS

Website

www.firebirdsql.org

www.microsoft.com/en-us/sql-server

www.oracle.com/database

splicemachine.com

trino.io

Technical documentation

www.firebirdsql.org/en/reference-manuals

learn.microsoft.com/en-US/sql/sql-server

docs.oracle.com/en/database

splicemachine.com/how-it-works

trino.io/broadcast
trino.io/docs/current

Developer

Firebird Foundation

Microsoft

Oracle

Splice Machine

Trino Software Foundation

Initial release

2000

As fork of Borland's InterBase

1989

1980

2014

2012

2020 rebranded from PrestoSQL

Current release

5.0.1, August 2024

SQL Server 2022, November 2022

23c, September 2023

3.1, March 2021

License

Commercial or Open Source

Open Source

Initial Developer's Public License

commercial

restricted free version is available

commercial

restricted free version is available

Open Source

AGPL 3.0, commercial license available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C and C++

C++

C and C++

Java

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
OS X
Solaris
Windows

Linux
macOS

for devlopment

Data scheme

yes

Schemaless in JSON and XML columns

yes

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

depending on connected data-source

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
Native Spark Datasource
ODBC

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

PSQL

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

PL/SQL

also stored procedures in Java possible

yes

Java

yes, depending on connected data-source

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding, horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

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

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

depending on connected data-source

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

SQL standard access control

More information provided by the system vendor

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