DBMS > ClickHouse vs. Google Cloud Firestore vs. GraphDB vs. Kinetica vs. PostgreSQL
System Properties Comparison ClickHouse vs. Google Cloud Firestore vs. GraphDB vs. Kinetica vs. PostgreSQL
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| Name | ClickHouse Xexclude from comparison | Google Cloud Firestore Xexclude from comparison | GraphDB  former name: OWLIM Xexclude from comparison | Kinetica 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. | Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products. | Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL. | 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 | Document store | Graph DBMS RDF store | 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 AgeSpatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | clickhouse.com | firebase.google.com/products/firestore | www.ontotext.com | www.kinetica.com | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | clickhouse.com/docs | firebase.google.com/docs/firestore | graphdb.ontotext.com/documentation | docs.kinetica.com | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Social network pages |      | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Clickhouse Inc. | Ontotext | Kinetica | PostgreSQL Global Development Group www.postgresql.org/developer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2016 | 2017 | 2000 | 2012 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | v24.3.2.23-lts, April 2024 | 10.4, October 2023 | 7.1, August 2021 | 16.2, February 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | Open Source Apache 2.0 | commercial | commercial Some plugins of GraphDB Workbench are open sourced | commercial | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | C++ | Java | C, C++ | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | FreeBSD Linux macOS | hosted | All OS with a Java VM Linux OS X Windows | Linux | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes | schema-free | schema-free and OWL/RDFS-schema support; RDF shapes | 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 | no | no | no | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | Close to ANSI SQL (SQL/JSON + extensions) | no | stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC | SQL-like DML and DDL statements | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | gRPC HTTP REST JDBC MySQL wire protocol ODBC PostgreSQL wire protocol Proprietary protocol | Android gRPC (using protocol buffers) API iOS JavaScript API RESTful HTTP API | GeoSPARQL GraphQL GraphQL Federation Java API JDBC RDF4J API RDFS RIO Sail API Sesame REST HTTP Protocol SPARQL 1.1 | JDBC ODBC RESTful HTTP API | 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 | Go Java JavaScript JavaScript (Node.js) Objective-C Python | .Net C# Clojure Java JavaScript (Node.js) PHP Python Ruby Scala | C++ Java JavaScript (Node.js) Python | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | yes | yes, Firebase Rules & Cloud Functions | well-defined plugin interfaces; JavaScript server-side extensibility | user defined functions | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | no | yes, with Cloud Functions | 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 | key based and custom | Sharding | none | 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 | Multi-source replication | 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 | Using Cloud Dataflow | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency | Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request) | Immediate Consistency or Eventual Consistency depending on configuration | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | no | yes Constraint checking | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | yes | ACID | no | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | 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 GPU vRAM or System RAM | 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, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth. | Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on. | Access rights for users and roles on table level | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| ClickHouse | Google Cloud Firestore | GraphDB former name: OWLIM | Kinetica | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | Ontotext GraphDB is a semantic database engine that allows organizations to build... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | Metadata enrichment and management, linked data publishing, semantic inferencing... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Key customers | GraphDB provides a platform for building next-generation AI and Knowledge Graph... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Market metrics | GraphDB is the most utilized semantic triplestore for mission-critical enterprise... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| News | Scaling Understanding with the Help of Feedback Loops, Knowledge Graphs and NLP How Knowledge Graphs Power Data Mesh and Data Fabric Building Smarter Financial Services: The Role of Semantic Technologies, Knowledge Graphs and Generative AI Using GraphDB’s Natural Language Interface to Talk with Your Content Choosing A Graph Data Model to Best Serve Your Use Case | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 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 | Instaclustr: Fully Hosted & Managed PostgreSQL » more SharePlex is the reliable and affordable data replication solution for PostgreSQL migrations, high availability and more. » 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 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 Navicat Monitor is a safe, simple and agentless remote server monitoring tool for PostgreSQL and many other database management systems. » 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 Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools. » more Navicat for PostgreSQL is an easy-to-use graphical tool for PostgreSQL database development. » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| ClickHouse | Google Cloud Firestore | GraphDB former name: OWLIM | Kinetica | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | Cloud-based DBMS's popularity grows at high rates | 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 ... A 1000x Faster Database Solution: ClickHouse’s Aaron Katz From Open Source to SaaS: the Journey of ClickHouse TikTok Parent Open Sources Real-Time Data Warehouse provided by Google News Realtime vs Cloud Firestore: Which Firebase Database to go? Google's AI-First Strategy Brings Vector Support To Cloud Databases Google’s Firebase gets AI extensions, opens up its marketplace Google's Cloud Firestore is now generally available Google's Cloud-Native NoSQL Database Cloud Firestore Is Now Generally Available provided by Google News Ontotext's GraphDB Solution is Now Available on the Microsoft Azure Marketplace Ontotext Unveils GraphDB 10.4 with Enhanced AWS Integration and ChatGPT Connector Ontotext GraphDB is available on Azure, delivers rich knowledge graph experience Ontotext Platform 3.0 for Enterprise Knowledge Graphs Released Ontotext's GraphDB 8.10 Makes Knowledge Graph Experience Faster and Richer provided by Google News Kinetica Elevates RAG with Fast Access to Real-Time Data Kinetica Delivers Real-Time Vector Similarity Search 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 Leveraging PostgreSQL for Cutting-Edge Generative AI Applications: Insights from Google's Product Managers Handle tables without primary keys while creating Amazon Aurora PostgreSQL zero-ETL integrations with Amazon ... Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need PostgreSQL or MySQL: What Should I Choose for My Full-Stack Project? Breaking Boundaries: PostgreSQL 16 is now available on IBM Cloud provided by Google News | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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