DBMS > BigchainDB vs. Firebird vs. Heroic vs. HyperSQL vs. Tarantool

System Properties Comparison BigchainDB vs. Firebird vs. Heroic vs. HyperSQL vs. Tarantool

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

Primary database model

Document store
Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Website

www.bigchaindb.com

www.firebirdsql.org

github.com/spotify/heroic

hsqldb.org

www.tarantool.io

Technical documentation

bigchaindb.readthedocs.io/en/latest

www.firebirdsql.org/en/reference-manuals

spotify.github.io/heroic

hsqldb.org/web/hsqlDocsFrame.html

www.tarantool.io/en/doc

Developer

Firebird Foundation

Spotify

Initial release

2016

2000

As fork of Borland's InterBase

2014

2001

2008

Current release

5.0.0, January 2024

2.7.2, June 2023

2.10.0, May 2022

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Initial Developer's Public License

Open Source

Apache 2.0

Open Source

based on BSD license

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

Python

C and C++

Java

C and C++

Server operating systems

Linux

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

BSD
Linux
macOS

Data scheme

schema-free

yes

schema-free

yes

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

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.

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

Full-featured ANSI SQL support

APIs and other access methods

CLI Client
RESTful HTTP API

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

Open binary protocol

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC
Java

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

Server-side scripts

Stored procedures

PSQL

Java, SQL

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

Sharding

none

Sharding

none

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

selectable replication factor

Source-replica replication

yes

none

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

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

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,with MongoDB ord RethinkDB

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

yes

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

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

show all

Recent citations in the news

Exploring the 10 BEST Python Libraries for Blockchain Applications
9 September 2023, DataDrivenInvestor

Using BigchainDB: A Database with Blockchain Characteristics
20 January 2022, Open Source For You

Blockchain Database Startup BigchainDB Raises €3 Million
27 September 2016, CoinDesk

ascribe announces scalable blockchain database BigchainDB - CoinReport
13 February 2016, CoinReport

7 blockchain firms join Bosch led GAIA-X consortium for vehicle identity
13 September 2022, Ledger Insights

provided by Google News

DoNot Team's New Firebird Backdoor Hits Pakistan and Afghanistan
23 October 2023, The Hacker News

12 Top Open Source Databases to Consider
1 May 2024, TechTarget

FIREBIRD'S HUBBARD TALKS DATA, AI, TIKTOK
14 December 2023, HITS Daily Double

Firebird - Analyst, Digital Marketing (US)
23 February 2024, Music Business Worldwide

Exploring the Firebird Database
9 August 2023, Open Source For You

provided by Google News

HyperSQL DataBase flaw leaves library vulnerable to RCE
24 October 2022, The Daily Swig

Introduction to JDBC with HSQLDB tutorial
14 November 2022, TheServerSide.com

provided by Google News

Deploying Tarantool Cartridge applications with zero effort (Part 1)
16 December 2019, Хабр

VShard — horizontal scaling in Tarantool
7 March 2019, Хабр

Accelerating PHP connectors for Tarantool using Async, Swoole, and Parallel
18 December 2019, Хабр

provided by Google News

Share this page