DBMS > ArcadeDB vs. ClickHouse vs. FoundationDB vs. Hive vs. QuestDB

System Properties Comparison ArcadeDB vs. ClickHouse vs. FoundationDB vs. Hive vs. QuestDB

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

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.

Ordered key-value store. Core features are complimented by layers.

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

A high performance open source SQL database for time series data

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Time Series DBMS

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Website

arcadedb.com

clickhouse.com

github.com/apple/foundationdb

hive.apache.org

questdb.io

Technical documentation

docs.arcadedb.com

clickhouse.com/docs

apple.github.io/foundationdb

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

questdb.io/docs

Developer

Arcade Data

Clickhouse Inc.

FoundationDB

Apache Software Foundation

initially developed by Facebook

QuestDB Technology Inc

Initial release

2021

2016

2013

2012

2014

Current release

September 2021

v24.4.1.2088-stable, May 2024

6.2.28, November 2020

3.1.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2

Open Source

Apache 2.0

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.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

Implementation language

Java

C++

Java

Java (Zero-GC), C++, Rust

Server operating systems

All OS with a Java VM

FreeBSD
Linux
macOS

Linux
OS X
Windows

All OS with a Java VM

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

some layers support schemas

yes

schema-free via InfluxDB Line Protocol

Typing

predefined data types such as float or date

yes

some layers support typing

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

SQL-like query language, no joins

Close to ANSI SQL (SQL/JSON + extensions)

supported in specific SQL layer only

SQL-like DML and DDL statements

SQL with time-series extensions

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

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

JDBC
ODBC
Thrift

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Supported programming languages

Java

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

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C++
Java
PHP
Python

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Server-side scripts

Stored procedures

yes

in SQL-layer only

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

horizontal partitioning (by timestamps)

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

yes

selectable replication factor

Source-replica replication with eventual consistency

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Linearizable consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

in SQL-layer only

Transaction concepts

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

ACID

ACID for single-table writes

Concurrency

Support for concurrent manipulation of data

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

through memory mapped files

User concepts

Access control

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.

Access rights for users, groups and roles

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
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Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

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