DBMS > Amazon Redshift vs. ClickHouse vs. Kinetica vs. PostgreSQL
System Properties Comparison Amazon Redshift vs. ClickHouse vs. Kinetica vs. PostgreSQL
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Name | Amazon Redshift Xexclude from comparison | ClickHouse Xexclude from comparison | Kinetica Xexclude from comparison | PostgreSQL Xexclude from comparison | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Large scale data warehouse service for use with business intelligence tools | 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. | Fully vectorized database across both GPUs and CPUs | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS | Relational DBMS | Relational DBMS | 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 Time Series DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aws.amazon.com/redshift | clickhouse.com | www.kinetica.com | www.postgresql.org | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.aws.amazon.com/redshift | clickhouse.com/docs | docs.kinetica.com | www.postgresql.org/docs | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Amazon (based on PostgreSQL) | Clickhouse Inc. | Kinetica | PostgreSQL Global Development Group www.postgresql.org/developer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2012 | 2016 | 2012 | 1989 1989: Postgres, 1996: PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | v24.4.1.2088-stable, May 2024 | 7.1, August 2021 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | Open Source Apache 2.0 | commercial | Open Source BSD | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | no | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | C | C++ | C, C++ | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | FreeBSD Linux macOS | Linux | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | yes | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | 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 | restricted | yes | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes does not fully support an SQL-standard | Close to ANSI SQL (SQL/JSON + extensions) | SQL-like DML and DDL statements | yes standard with numerous extensions | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JDBC ODBC | gRPC HTTP REST JDBC MySQL wire protocol ODBC PostgreSQL wire protocol Proprietary protocol | JDBC ODBC RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | All languages supporting JDBC/ODBC | C# 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++ Java JavaScript (Node.js) Python | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | user defined functions in Python | yes | user defined functions | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | no | yes triggers when inserted values for one or more columns fall within a specified range | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | key based and custom | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes | Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages. | Source-replica replication | Source-replica replication other methods possible by using 3rd party extensions | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | no | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency | Immediate Consistency or Eventual Consistency depending on configuration | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes informational only, not enforced by the system | no | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no | no | ACID | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | 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 | yes | yes GPU vRAM or System RAM | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | 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. | Access rights for users and roles on table level | fine grained access rights according to SQL-standard | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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3rd parties | CData: Connect to Big Data & NoSQL through standard Drivers. » more | 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 | Instaclustr: Fully Hosted & Managed PostgreSQL » more Redgate webinars: A series of key topics for new PostgreSQL users. » more Navicat for PostgreSQL is an easy-to-use graphical tool for PostgreSQL database development. » more SharePlex is the reliable and affordable data replication solution for PostgreSQL migrations, high availability and more. » more Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools. » 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 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 Navicat Monitor is a safe, simple and agentless remote server monitoring tool for PostgreSQL and many other database management systems. » more pgDash: In-Depth PostgreSQL Monitoring. » 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Amazon Redshift | ClickHouse | Kinetica | PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Cloud-based DBMS's popularity grows at high rates The popularity of cloud-based DBMSs has increased tenfold in four years Increased popularity for consuming DBMS services out of the cloud | 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 How Swisscom automated Amazon Redshift as part of their One Data Platform solution using AWS CDK – Part 1 ... Amazon Redshift Serverless is now available in the AWS Middle East (UAE) region - AWS Amazon Redshift Serverless is now generally available in the AWS China (Ningxia) Region - AWS Integrate Tableau and Okta with Amazon Redshift using AWS IAM Identity Center | Amazon Web Services Amazon Redshift adds new AI capabilities, including Amazon Q, to boost efficiency and productivity | Amazon Web ... provided by Google News Why Clickhouse Should Be Your Next Database ClickHouse Cloud & Amazon S3 Express One Zone: Making a blazing fast analytical database even faster | Amazon ... Intel Xeon 6766E/6780E Sierra Forest vs. Ampere Altra Performance & Power Efficiency Review A 1000x Faster Database Solution: ClickHouse’s Aaron Katz From Open Source to SaaS: the Journey of ClickHouse provided by Google News Kinetica Delivers Real-Time Vector Similarity Search Kinetica Elevates RAG with Fast Access to Real-Time Data Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise Transforming spatiotemporal data analysis with GPUs and generative AI provided by Google News Timescale unveils high-performance AI vector database extensions for PostgreSQL PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions PostgreSQL Tutorial: Definition, Commands, & Features A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions Raise the bar on AI-powered app development with Azure Database for PostgreSQL provided by Google News |
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