DBMS > Apache Phoenix vs. Brytlyt vs. ClickHouse vs. TerminusDB

System Properties Comparison Apache Phoenix vs. Brytlyt vs. ClickHouse vs. TerminusDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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.

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Graph DBMS

Secondary database models

Time Series DBMS

Document store
RDF store

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

Technical documentation

phoenix.apache.org

docs.brytlyt.io

clickhouse.com/docs

terminusdb.github.io/terminusdb/#

Developer

Apache Software Foundation

Brytlyt

Clickhouse Inc.

DataChemist Ltd.

Initial release

2014

2016

2018

Current release

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

5.0, August 2023

v24.4.1.2088-stable, May 2024

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Implementation language

Java

C, C++ and CUDA

C++

Prolog, Rust

Server operating systems

Linux
Unix
Windows

Linux
OS X
Windows

FreeBSD
Linux
macOS

Linux

Data scheme

yes

late-bound, schema-on-read capabilities

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language (WOQL)

APIs and other access methods

JDBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

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

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

key based and custom

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

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

Journaling Streams

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

fine grained access rights according to SQL-standard

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.

Role-based access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.