DBMS > Firebird vs. Kinetica vs. Manticore Search vs. Neo4j vs. Snowflake

System Properties Comparison Firebird vs. Kinetica vs. Manticore Search vs. Neo4j vs. Snowflake

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

Multi-storage database for search, including full-text search.

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

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Time Series DBMS

using the Manticore Columnar Library

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	0.29
Rank	#302	Overall
	#21	Search engines

Score	44.89
Rank	#21	Overall
	#1	Graph DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

Technical documentation

www.firebirdsql.org/en/reference-manuals

docs.kinetica.com

manual.manticoresearch.com

neo4j.com/docs

docs.snowflake.net/manuals/index.html

Developer

Firebird Foundation

Kinetica

Manticore Software

Neo4j, Inc.

Snowflake Computing Inc.

Initial release

2000

As fork of Borland's InterBase

2012

2017

2007

2014

Current release

5.0.0, January 2024

7.1, August 2021

6.0, February 2023

5.20, May 2024

License

Commercial or Open Source

Open Source

Initial Developer's Public License

commercial

Open Source

GPL version 2

Open Source

GPL version3, commercial licenses available

commercial

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++

C++

Java, Scala

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux

FreeBSD
Linux
macOS
Windows

Linux

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

hosted

Data scheme

yes

Fixed schema

schema-free and schema-optional

yes

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

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

yes

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

yes

SQL-like DML and DDL statements

SQL-like query language

yes

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
ODBC
RESTful HTTP API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

CLI Client
JDBC
ODBC

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

PSQL

user defined functions

yes

User defined Procedures and Functions

user defined functions

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

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

yes using Neo4j Fabric

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Synchronous replication based on Galera library

Causal Clustering using Raft protocol

available in in Enterprise Version only

yes

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

yes

isolated transactions for atomic changes and binary logging for safe writes

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

The original contents of fields are not stored in the Manticore index.

yes

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

More information provided by the system vendor

Specific characteristics

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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