DBMS > ClickHouse vs. CouchDB vs. Google Cloud Bigtable vs. PostgreSQL
System Properties Comparison ClickHouse vs. CouchDB vs. Google Cloud Bigtable vs. PostgreSQL
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| Name | ClickHouse Xexclude from comparison | CouchDB  stands for "Cluster Of Unreliable Commodity Hardware" Xexclude from comparison | Google Cloud Bigtable Xexclude from comparison | PostgreSQL Xexclude from comparison | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones. | Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail. | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Relational DBMS | Document store | Key-value store Wide column store | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Time Series DBMS | Spatial DBMS using the Geocouch extension | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | clickhouse.com | couchdb.apache.org | cloud.google.com/bigtable | www.postgresql.org | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | clickhouse.com/docs | docs.couchdb.org/en/stable | cloud.google.com/bigtable/docs | www.postgresql.org/docs | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Clickhouse Inc. | Apache Software Foundation Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2016 | 2005 | 2015 | 1989 1989: Postgres, 1996: PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | v24.4.1.2088-stable, May 2024 | 3.3.3, December 2023 | 16.2, February 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | Open Source Apache 2.0 | Open Source Apache version 2 | commercial | Open Source BSD | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | no | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | C++ | Erlang | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | FreeBSD Linux macOS | Android BSD Linux OS X Solaris Windows | hosted | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes | schema-free | schema-free | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | no | no | 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. | no | no | no | yes specific XML-type available, but no XML query functionality. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes via views | no | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | Close to ANSI SQL (SQL/JSON + extensions) | no | no | yes standard with numerous extensions | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | gRPC HTTP REST JDBC MySQL wire protocol ODBC PostgreSQL wire protocol Proprietary protocol | RESTful HTTP/JSON API | gRPC (using protocol buffers) API HappyBase (Python library) HBase compatible API (Java) | ADO.NET JDBC native C library ODBC streaming API for large objects | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | C# 3rd party library C++ Elixir 3rd party libraryGo 3rd party libraryJava 3rd party libraryJavaScript (Node.js) 3rd party libraryKotlin 3rd party libraryNim 3rd party libraryPerl 3rd party libraryPHP 3rd party libraryPython 3rd party libraryR 3rd party libraryRuby 3rd party libraryRust Scala 3rd party library | C C# ColdFusion Erlang Haskell Java JavaScript Lisp Lua Objective-C OCaml Perl PHP PL/SQL Python Ruby Smalltalk | C# C++ Go Java JavaScript (Node.js) Python | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | yes | View functions in JavaScript | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | no | yes | no | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | key based and custom | Sharding improved architecture with release 2.0 | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages. | Multi-source replication Source-replica replication | Internal replication in Colossus, and regional replication between two clusters in different zones | Source-replica replication other methods possible by using 3rd party extensions | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no | yes | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Eventual Consistency | Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters) | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | no | no | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | no atomic operations within a single document possible | Atomic single-row operations | ACID | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes strategy: optimistic locking | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | no | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 can be defined per database | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | fine grained access rights according to SQL-standard | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 3rd parties | DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale. » more Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics. » more | Navicat for PostgreSQL is an easy-to-use graphical tool for PostgreSQL database development. » more Navicat Monitor is a safe, simple and agentless remote server monitoring tool for PostgreSQL and many other database management systems. » more Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools. » more Instaclustr: Fully Hosted & Managed PostgreSQL » more Redgate webinars: A series of key topics for new PostgreSQL users. » more CYBERTEC is your professional partner in PostgreSQL topics for over 20 years. As our main aim is to be your single-source all-in-one IT service provider, we offer a wide range of products and services. Visit our website for more details. » more pgDash: In-Depth PostgreSQL Monitoring. » more Fujitsu Enterprise Postgres: An Enterprise Grade PostgreSQL with the flexibility of a hybrid cloud solution combined with industry leading security, availability and performance. » more Timescale: Calling all PostgreSQL users – the 2023 State of PostgreSQL survey is now open! Share your favorite extensions, preferred frameworks, community experiences, and more. Take the survey today! » more SharePlex is the reliable and affordable data replication solution for PostgreSQL migrations, high availability and more. » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| ClickHouse | CouchDB stands for "Cluster Of Unreliable Commodity Hardware" | Google Cloud Bigtable | PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 Monitoring PostgreSQL with Redgate Monitor Why Clickhouse Should Be Your Next Database ClickHouse Cloud & Amazon S3 Express One Zone: Making a blazing fast analytical database even faster | Amazon ... From Open Source to SaaS: the Journey of ClickHouse Snowflake vs. BigQuery vs. ClickHouse: Mastering Cost-Effective Business Analytics ClickHouse Announces Launch of ClickPipes provided by Google News How to install the CouchDB NoSQL database on Debian Server 11 IBM Cloudant pulls plan to fund new foundational layer for CouchDB CouchDB 3.0 puts safety first CouchDB 3.0 ends admin party era • DEVCLASS How to Connect Your Flask App With CouchDB: A NoSQL Database - MUO provided by Google News Google's AI-First Strategy Brings Vector Support To Cloud Databases What is Google Bigtable? | Definition from TechTarget Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs Review: Google Bigtable scales with ease Google Cloud makes it cheaper to run smaller workloads on Bigtable provided by Google News AGEDB Technology Launches PGTS - PostgreSQL Tech-Support PostgreSQL Security Flaws Let Attackers Execute Code Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need Automatically Generate Types for Your PostgreSQL Database Your MySQL 5.7 and PostgreSQL 11 databases will be automatically enrolled into Amazon RDS Extended Support ... provided by Google News | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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