DBMS > Couchbase vs. Firebird vs. Google Cloud Firestore vs. Hyprcubd vs. InfinityDB

System Properties Comparison Couchbase vs. Firebird vs. Google Cloud Firestore vs. Hyprcubd vs. InfinityDB

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

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

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Serverless Time Series DBMS

A Java embedded Key-Value Store which extends the Java Map interface

Primary database model

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Website

www.couchbase.com

www.firebirdsql.org

firebase.google.com/products/firestore

hyprcubd.com (offline)

boilerbay.com

Technical documentation

docs.couchbase.com

www.firebirdsql.org/en/reference-manuals

firebase.google.com/docs/firestore

boilerbay.com/infinitydb/manual

Developer

Couchbase, Inc.

Firebird Foundation

Google

Hyprcubd, Inc.

Boiler Bay Inc.

Initial release

2011

2000

As fork of Borland's InterBase

2017

2002

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

5.0.0, January 2024

4.0

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Initial Developer's Public License

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, C++, Go and Erlang

C and C++

Java

Server operating systems

Linux
OS X
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

hosted

All OS with a Java VM

Data scheme

schema-free

yes

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

SQL-like query language

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

gRPC (https)

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

Java

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

PSQL

yes, Firebase Rules & Cloud Functions

Triggers

yes

via the TAP protocol

yes

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Source-replica replication

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Eventual Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

yes

ACID

Optimistic locking for transactions; no isolation for bulk loads

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.

yes

Ephemeral buckets

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Users with fine-grained authorization concept

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

token access

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