DBMS > ClickHouse vs. QuestDB vs. RocksDB vs. Vertica

System Properties Comparison ClickHouse vs. QuestDB vs. RocksDB vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

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.

A high performance open source SQL database for time series data

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Column oriented

Secondary database models

Time Series DBMS

Relational DBMS

Spatial DBMS
Time Series DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

Technical documentation

clickhouse.com/docs

questdb.io/docs

github.com/facebook/rocksdb/wiki

vertica.com/documentation

Developer

Clickhouse Inc.

QuestDB Technology Inc

Facebook, Inc.

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2016

2014

2013

2005

Current release

v24.4.1.2088-stable, May 2024

9.2.1, May 2024

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

BSD

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

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.
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.

Implementation language

C++

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

C++

Server operating systems

FreeBSD
Linux
macOS

Linux
macOS
Windows

Linux

Data scheme

yes

schema-free via InfluxDB Line Protocol

schema-free

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL with time-series extensions

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

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

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

C++ API
Java API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

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

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

over HTTP

C
C++
Go
Java
Perl
Python
Ruby

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

key based and custom

horizontal partitioning (by timestamps)

horizontal partitioning

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication with eventual consistency

yes

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID for single-table writes

yes

ACID

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

yes

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.

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

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

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

Cost-based models and subscription-based models are both available. One license is...
» more

News

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6 May 2024

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12 April 2024

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8 April 2024

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