DBMS > Apache Phoenix vs. BigObject vs. Cachelot.io vs. ClickHouse vs. DuckDB

System Properties Comparison Apache Phoenix vs. BigObject vs. Cachelot.io vs. ClickHouse vs. DuckDB

Editorial information provided by DB-Engines

Name

Description

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

Analytic DBMS for real-time computations and queries

In-memory caching system

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	4.57
Rank	#74	Overall
	#40	Relational DBMS

Website

Technical documentation

Developer

Apache Software Foundation

BigObject, Inc.

Clickhouse Inc.

Initial release

2014

2015

2016

2018

Current release

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

v24.4.1.2088-stable, May 2024

0.10, February 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community edition available

Open Source

Simplified BSD License

Open Source

Apache 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Server operating systems

Linux
Unix
Windows

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

FreeBSD
Linux
OS X

FreeBSD
Linux
macOS

server-less

Data scheme

yes

late-bound, schema-on-read capabilities

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

JDBC

fluentd
ODBC
RESTful HTTP API

Memcached protocol

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

Supported programming languages

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

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

Server-side scripts

Stored procedures

user defined functions

Lua

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

key based and custom

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

yes, multi-version concurrency control (MVCC)

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

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

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

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