DBMS > Firebird vs. GeoMesa vs. Heroic vs. TerarkDB

System Properties Comparison Firebird vs. GeoMesa vs. Heroic vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

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

Score	19.46
Rank	#30	Overall
	#18	Relational DBMS

Score	0.78
Rank	#214	Overall
	#4	Spatial DBMS

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

www.firebirdsql.org

www.geomesa.org

github.com/spotify/heroic

github.com/bytedance/terarkdb

Technical documentation

www.firebirdsql.org/en/reference-manuals

www.geomesa.org/documentation/stable/user/index.html

spotify.github.io/heroic

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Firebird Foundation

CCRi and others

Spotify

ByteDance, originally Terark

Initial release

2000

As fork of Borland's InterBase

2014

2016

Current release

5.0.1, August 2024

5.0.1, July 2024

License

Commercial or Open Source

Open Source

Initial Developer's Public License

Open Source

Apache License 2.0

Open Source

Apache 2.0

commercial

restricted open source version 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++

Scala

Java

C++

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Data scheme

yes

schema-free

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

via Elasticsearch

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

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

C++ API
Java API

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

PSQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

depending on storage layer

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Eventual Consistency
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

In-memory capabilities

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

depending on storage layer

yes

User concepts

Access control

Users with fine-grained authorization concept

yes

depending on the DBMS used for storage

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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