DBMS > Firebird vs. Greenplum vs. jBASE vs. Tarantool

System Properties Comparison Firebird vs. Greenplum vs. jBASE vs. Tarantool

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Editorial information provided by DB-Engines

Name

Description

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

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

A robust multi-value DBMS comprising development tools and middleware

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Relational DBMS

Multivalue DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

with Tarantool/GIS extension

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

Score	19.46
Rank	#30	Overall
	#18	Relational DBMS

Score	7.71
Rank	#46	Overall
	#29	Relational DBMS

Score	1.36
Rank	#157	Overall
	#3	Multivalue DBMS

Score	1.63
Rank	#139	Overall
	#25	Document stores
	#24	Key-value stores
	#65	Relational DBMS

Website

www.firebirdsql.org

greenplum.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.tarantool.io

Technical documentation

www.firebirdsql.org/en/reference-manuals

docs.greenplum.org

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

www.tarantool.io/en/doc

Developer

Firebird Foundation

Pivotal Software Inc.

Rocket Software (formerly Zumasys)

Initial release

2000

As fork of Borland's InterBase

2005

1991

2008

Current release

5.0.1, August 2024

7.0.0, September 2023

5.7

2.10.0, May 2022

License

Commercial or Open Source

Open Source

Initial Developer's Public License

Open Source

Apache 2.0

commercial

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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++

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux

AIX
Linux
Windows

BSD
Linux
macOS

Data scheme

yes

schema-free

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

optional

string, double, decimal, uuid, integer, blob, boolean, datetime

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

since Version 4.2

yes

Secondary indexes

yes

SQL

Support of SQL

yes

Embedded SQL for jBASE in BASIC

Full-featured ANSI SQL support

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
ODBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Open binary protocol

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C
Java
Perl
Python
R

.Net
Basic
Jabbascript
Java

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

PSQL

yes

Lua, C and SQL stored procedures

Triggers

yes

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

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

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources

DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

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