DBMS > Firebird vs. Kinetica vs. Neo4j vs. Snowflake vs. TerminusDB

System Properties Comparison Firebird vs. Kinetica vs. Neo4j vs. Snowflake vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

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

Fully vectorized database across both GPUs and CPUs

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Cloud-based data warehousing service for structured and semi-structured data

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
RDF store

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

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	44.89
Rank	#21	Overall
	#1	Graph DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

Technical documentation

www.firebirdsql.org/en/reference-manuals

docs.kinetica.com

neo4j.com/docs

docs.snowflake.net/manuals/index.html

terminusdb.github.io/terminusdb/#

Developer

Firebird Foundation

Kinetica

Neo4j, Inc.

Snowflake Computing Inc.

DataChemist Ltd.

Initial release

2000

As fork of Borland's InterBase

2012

2007

2014

2018

Current release

5.0.0, January 2024

7.1, August 2021

5.20, May 2024

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Initial Developer's Public License

commercial

Open Source

GPL version3, commercial licenses available

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

C and C++

C, C++

Java, Scala

Prolog, Rust

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

hosted

Linux

Data scheme

yes

schema-free and schema-optional

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

SQL-like query language (WOQL)

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
ODBC
RESTful HTTP API

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

CLI Client
JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

JavaScript
Python

Server-side scripts

Stored procedures

PSQL

user defined functions

yes

User defined Procedures and Functions

user defined functions

yes

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

via event handler

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes using Neo4j Fabric

yes

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Causal Clustering using Raft protocol

available in in Enterprise Version only

yes

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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 journaling

In-memory capabilities

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

yes

GPU vRAM or System RAM

User concepts

Access control

Users with fine-grained authorization concept

Access rights for users and roles on table level

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

Users with fine-grained authorization concept, user roles and pluggable authentication

Role-based access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
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Market metrics

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
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Licensing and pricing models

GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.