DBMS > ClickHouse vs. Google Cloud Bigtable vs. GridDB vs. InfluxDB vs. IRONdb

System Properties Comparison ClickHouse vs. Google Cloud Bigtable vs. GridDB vs. InfluxDB vs. IRONdb

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Scalable in-memory time series database optimized for IoT and Big Data

DBMS for storing time series, events and metrics

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Primary database model

Relational DBMS

Key-value store
Wide column store

Time Series DBMS

Secondary database models

Time Series DBMS

Key-value store
Relational DBMS

Spatial DBMS

with GEO package

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Website

clickhouse.com

cloud.google.com/bigtable

griddb.net

www.influxdata.com/products/influxdb-overview

www.circonus.com/solutions/time-series-database/

Technical documentation

clickhouse.com/docs

cloud.google.com/bigtable/docs

docs.griddb.net

docs.influxdata.com/influxdb

docs.circonus.com/irondb/category/getting-started

Developer

Clickhouse Inc.

Google

Toshiba Corporation

Circonus LLC.

Initial release

2016

2015

2013

2017

Current release

v24.4.1.2088-stable, May 2024

5.1, August 2022

2.7.6, April 2024

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

MIT-License; commercial enterprise version available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

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.
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++

C and C++

Server operating systems

FreeBSD
Linux
macOS

hosted

Linux

Linux
OS X

through Homebrew

Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

Numeric data and Strings

yes

text, numeric, histograms

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

Close to ANSI SQL (SQL/JSON + extensions)

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like query language

SQL-like query language (Circonus Analytics Query Language: CAQL)

APIs and other access methods

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

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

HTTP API
JSON over UDP

HTTP API

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

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

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

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

yes

yes, in Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

in enterprise version only

Automatic, metric affinity per node

Replication methods

Methods for redundantly storing data on multiple nodes

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

Internal replication in Colossus, and regional replication between two clusters in different zones

Source-replica replication

selectable replication factor

in enterprise version only

configurable replication factor, datacenter aware

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate consistency within container, eventual consistency across containers

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

ACID at container level

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

Depending on used storage engine

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 based on Google Cloud Identity and Access Management (IAM)

Access rights for users can be defined per database

simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
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InfluxData is the creator of InfluxDB , the open source time series database. It...
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Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
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Time to Value InfluxDB is available in all the popular languages and frameworks,...
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Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
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IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
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Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
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InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
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Market metrics

GitHub trending repository
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Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
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Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

Open source core with closed source clustering available either on-premise or on...
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