DBMS > Firebird vs. Lovefield vs. MaxDB vs. Vertica

System Properties Comparison Firebird vs. Lovefield vs. MaxDB vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

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

Embeddable relational database for web apps written in pure JavaScript

A robust and reliable RDBMS optimized to run all major SAP solutions

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	19.46
Rank	#30	Overall
	#18	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	2.15
Rank	#115	Overall
	#55	Relational DBMS

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Website

www.firebirdsql.org

google.github.io/lovefield

maxdb.sap.com

www.vertica.com

Technical documentation

www.firebirdsql.org/en/reference-manuals

github.com/google/lovefield/blob/master/docs/spec_index.md

maxdb.sap.com/documentation

vertica.com/documentation

Developer

Firebird Foundation

Google

SAP, acquired from Software AG (Adabas-D) in 1997

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2000

As fork of Borland's InterBase

2014

1984

2005

Current release

5.0.1, August 2024

2.1.12, February 2017

7.9.10.12, February 2024

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Initial Developer's Public License

Open Source

Apache 2.0

commercial

Limited community edition free

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

JavaScript

C++

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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.

Secondary indexes

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

ADO.NET
JDBC
ODBC
WebDAV

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

JavaScript

.Net
C#
Java
Perl
PHP
Python

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

Server-side scripts

Stored procedures

PSQL

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

Using read-only observers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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