DBMS > Apache Phoenix vs. Couchbase vs. Firebird vs. Hazelcast

System Properties Comparison Apache Phoenix vs. Couchbase vs. Firebird vs. Hazelcast

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Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

A widely adopted in-memory data grid

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

Document store

JSON support with IMDG 3.12

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Website

Technical documentation

phoenix.apache.org

docs.couchbase.com

www.firebirdsql.org/en/reference-manuals

hazelcast.org/imdg/docs

Developer

Apache Software Foundation

Couchbase, Inc.

Firebird Foundation

Hazelcast

Initial release

2014

2011

2000

As fork of Borland's InterBase

2008

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

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

5.0.0, January 2024

5.3.6, November 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

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

Open Source

Initial Developer's Public License

Open Source

Apache Version 2; commercial licenses available

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

C, C++, Go and Erlang

C and C++

Java

Server operating systems

Linux
Unix
Windows

Linux
OS X
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

All OS with a Java VM

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

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.

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

yes

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

yes

SQL-like query language

APIs and other access methods

JDBC

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

JCache
JPA
Memcached protocol
RESTful HTTP API

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

.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

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

user defined functions

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

PSQL

yes

Event Listeners, Executor Services

Triggers

yes

via the TAP protocol

yes

Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

including cross data center replication
Source-replica replication

Source-replica replication

yes

Replicated Map

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

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

yes

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

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

Users with fine-grained authorization concept

Role-based access control

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