DBMS > ClickHouse vs. PostgreSQL vs. QuestDB vs. SingleStore vs. Spark SQL
System Properties Comparison ClickHouse vs. PostgreSQL vs. QuestDB vs. SingleStore vs. Spark SQL
Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Name | ClickHouse Xexclude from comparison | PostgreSQL Xexclude from comparison | QuestDB Xexclude from comparison | SingleStore former name was MemSQL Xexclude from comparison | Spark SQL 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. | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | A high performance open source SQL database for time series data | MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type | Spark SQL is a component on top of 'Spark Core' for structured data processing | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Time Series DBMS | Relational DBMS | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Time Series DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | Relational DBMS | Document store Spatial DBMS Time Series DBMS Vector DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|
|
|
|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Website | clickhouse.com | www.postgresql.org | questdb.io | www.singlestore.com | spark.apache.org/sql | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | clickhouse.com/docs | www.postgresql.org/docs | questdb.io/docs | docs.singlestore.com | spark.apache.org/docs/latest/sql-programming-guide.html | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Clickhouse Inc. | PostgreSQL Global Development Group www.postgresql.org/developer | QuestDB Technology Inc | SingleStore Inc. | Apache Software Foundation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2016 | 1989 1989: Postgres, 1996: PostgreSQL | 2014 | 2013 | 2014 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | v24.4.1.2088-stable, May 2024 | 16.3, May 2024 | 8.5, January 2024 | 3.5.0 ( 2.13), September 2023 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache 2.0 | Open Source BSD | Open Source Apache 2.0 | commercial free developer edition available | Open Source Apache 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. |
| Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools. | SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C++ | C | Java (Zero-GC), C++, Rust | C++, Go | Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | FreeBSD Linux macOS | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux macOS Windows | Linux 64 bit version required | Linux OS X Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | yes | yes schema-free via InfluxDB Line Protocol | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | 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 | yes specific XML-type available, but no XML query functionality. | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | Close to ANSI SQL (SQL/JSON + extensions) | yes standard with numerous extensions | SQL with time-series extensions | yes but no triggers and foreign keys | SQL-like DML and DDL statements | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | gRPC HTTP REST JDBC MySQL wire protocol ODBC PostgreSQL wire protocol Proprietary protocol | ADO.NET JDBC native C library ODBC streaming API for large objects | HTTP REST InfluxDB Line Protocol (TCP/UDP) JDBC PostgreSQL wire protocol | Cluster Management API as HTTP Rest and CLI HTTP API JDBC MongoDB API ODBC | JDBC ODBC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | 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 | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | C PostgreSQL driver C++ Go Java JavaScript (Node.js) Python Rust over HTTP | Bash C C# Java JavaScript (Node.js) Python | Java Python R Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | key based and custom | partitioning by range, list and (since PostgreSQL 11) by hash | horizontal partitioning (by timestamps) | Sharding hash partitioning | yes, utilizing Spark Core | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 other methods possible by using 3rd party extensions | Source-replica replication with eventual consistency | Source-replica replication stores two copies of each physical data partition on two separate nodes | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | no | no | no can define user-defined aggregate functions for map-reduce-style calculations | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency | Immediate Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | ACID | ACID for single-table writes | ACID | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes, multi-version concurrency control (MVCC) | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log. | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | no | yes through memory mapped files | yes | 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. | fine grained access rights according to SQL-standard | Fine grained access control via users, groups and roles | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
ClickHouse | PostgreSQL | QuestDB | SingleStore former name was MemSQL | Spark SQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Relational model with native time series support Column-based storage and time partitioned... » more | SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations... » more | SingleStore’s competitive advantages include: Easy and Simplified Architecture with... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Financial tick data Industrial IoT Application Metrics Monitoring » more | Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,... » more | IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Customers in various industries worldwide including US and International Industry... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud » more | F ree Tier and Enterprise Edition » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | QuestDB and Raspberry Pi 5 benchmark, a pocket-sized powerhouse Build your own resource monitor with QuestDB and Grafana Does "vpmovzxbd" Scare You? Here's Why it Doesn't Have To Create an ADS-B flight radar with QuestDB and a Raspberry Pi Build a temperature IoT sensor with Raspberry Pi Pico & QuestDB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
We invite representatives of system vendors to contact us for updating and extending the system information, | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Related products and services | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
3rd parties | Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics. » more DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale. » more | Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools.
» more Instaclustr: Fully Hosted & Managed PostgreSQL » 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 pgDash: In-Depth PostgreSQL Monitoring. » 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 Redgate webinars: A series of key topics for new PostgreSQL users. » 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 SharePlex is the reliable and affordable data replication solution for PostgreSQL migrations, high availability and more. » more Navicat for PostgreSQL is an easy-to-use graphical tool for PostgreSQL database development. » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
We invite representatives of vendors of related products to contact us for presenting information about their offerings here. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
ClickHouse | PostgreSQL | QuestDB | SingleStore former name was MemSQL | Spark SQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | 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 | Turbocharge Your Application Development Using WebAssembly With SingleStoreDB Cloud-Based Analytics With SingleStoreDB SingleStore: The Increasing Momentum of Multi-Model Database Systems | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Conferences, events and webinars | Monitoring PostgreSQL with Redgate Monitor | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | Why Clickhouse Should Be Your Next Database ClickHouse Cloud & Amazon S3 Express One Zone: Making a blazing fast analytical database even faster | Amazon ... A 1000x Faster Database Solution: ClickHouse’s Aaron Katz From Open Source to SaaS: the Journey of ClickHouse ClickHouse Announces Launch of ClickPipes provided by Google News | Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need Automatically Generate Types for Your PostgreSQL Database General availability: Microsoft Entra ID integration with Azure Cosmos DB for PostgreSQL | Azure updates Your MySQL 5.7 and PostgreSQL 11 databases will be automatically enrolled into Amazon RDS Extended Support ... Why PostgreSQL Is the Bedrock for the Future of Data provided by Google News | AWS Marketplace: QuestDB Cloud Comments QuestDB snares $12M Series A with hosted version coming soon SQL Extensions for Time-Series Data in QuestDB Read the Pitch Deck Database Startup QuestDB Used to Raise $12 Million QuestDB gets $12M Series A funding amid growing interest in time-series databases provided by Google News | SingleStore CEO sees little future for purpose-built vector databases Building a Modern Database: Nikita Shamgunov on Postgres and Beyond SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files SingleStore CEO on High-Speed Database Currents provided by Google News | Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services What is Apache Spark? The big data platform that crushed Hadoop Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024 Performant IPv4 Range Spark Joins | by Jean-Claude Cote 18 Top Big Data Tools and Technologies to Know About in 2024 provided by Google News |
Share this page