DBMS > Firebird vs. Hive vs. IBM Cloudant vs. Ignite vs. Snowflake

System Properties Comparison Firebird vs. Hive vs. IBM Cloudant vs. Ignite vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Database as a Service offering based on Apache CouchDB

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

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

Primary database model

Relational DBMS

Document store

Key-value store
Relational DBMS

Relational DBMS

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

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.firebirdsql.org

hive.apache.org

www.ibm.com/products/cloudant

ignite.apache.org

www.snowflake.com

Technical documentation

www.firebirdsql.org/en/reference-manuals

cwiki.apache.org/confluence/display/Hive/Home

cloud.ibm.com/docs/Cloudant

apacheignite.readme.io/docs

docs.snowflake.net/manuals/index.html

Developer

Firebird Foundation

Apache Software Foundation

initially developed by Facebook

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Apache Software Foundation

Snowflake Computing Inc.

Initial release

2000

As fork of Borland's InterBase

2012

2010

2015

2014

Current release

5.0.0, January 2024

3.1.3, April 2022

Apache Ignite 2.6

License

Commercial or Open Source

Open Source

Initial Developer's Public License

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

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.

Implementation language

C and C++

Java

Erlang

C++, Java, .Net

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

All OS with a Java VM

hosted

Linux
OS X
Solaris
Windows

hosted

Data scheme

yes

schema-free

yes

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

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

SQL

Support of SQL

yes

SQL-like DML and DDL statements

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
ODBC
Thrift

RESTful HTTP/JSON API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

CLI Client
JDBC
ODBC

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C++
Java
PHP
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

PSQL

yes

user defined functions and integration of map-reduce

View functions (Map-Reduce) in JavaScript

yes (compute grid and cache interceptors can be used instead)

user defined functions

Triggers

yes

yes (cache interceptors and events)

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

Multi-source replication
Source-replica replication

yes (replicated cache)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

yes

Optimistic locking

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.

yes

User concepts

Access control

Users with fine-grained authorization concept

Access rights for users, groups and roles

Access rights for users can be defined per database

Security Hooks for custom implementations

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

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