DBMS > Firebird vs. Geode vs. HEAVY.AI

System Properties Comparison Firebird vs. Geode vs. HEAVY.AI

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Editorial information provided by DB-Engines

Name

Description

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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Website

www.firebirdsql.org

geode.apache.org

github.com/heavyai/heavydb
www.heavy.ai

Technical documentation

www.firebirdsql.org/en/reference-manuals

geode.apache.org/docs

docs.heavy.ai

Developer

Firebird Foundation

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

HEAVY.AI, Inc.

Initial release

2000

As fork of Borland's InterBase

2002

2016

Current release

5.0.0, January 2024

1.1, February 2017

5.10, January 2022

License

Commercial or Open Source

Open Source

Initial Developer's Public License

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache Version 2; enterprise edition available

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

C and C++

Java

C++ and CUDA

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

All OS with a Java VM

the JDK (8 or later) is also required

Linux

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (OQL)

yes

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

Java Client API
Memcached protocol
RESTful HTTP API

JDBC
ODBC
Thrift
Vega

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

.Net
All JVM based languages
C++
Groovy
Java
Scala

All languages supporting JDBC/ODBC/Thrift
Python

Server-side scripts

Stored procedures

PSQL

user defined functions

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

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

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 per client and object definable

fine grained access rights according to SQL-standard

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