DBMS > Amazon DynamoDB vs. ClickHouse vs. Google Cloud Firestore vs. PostgreSQL vs. RDFox
System Properties Comparison Amazon DynamoDB vs. ClickHouse vs. Google Cloud Firestore vs. PostgreSQL vs. RDFox
| Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Name | Amazon DynamoDB Xexclude from comparison | ClickHouse Xexclude from comparison | Google Cloud Firestore Xexclude from comparison | PostgreSQL Xexclude from comparison | RDFox Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | Hosted, scalable database service by Amazon with the data stored in Amazons cloud | 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. | Widely used open source RDBMS  Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | High performance knowledge graph and semantic reasoning engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Document store Key-value store | Relational DBMS | Document store | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Graph DBMS RDF store | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Time Series DBMS | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | aws.amazon.com/dynamodb | clickhouse.com | firebase.google.com/products/firestore | www.postgresql.org | www.oxfordsemantic.tech | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.aws.amazon.com/dynamodb | clickhouse.com/docs | firebase.google.com/docs/firestore | www.postgresql.org/docs | docs.oxfordsemantic.tech | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Amazon | Clickhouse Inc. | PostgreSQL Global Development Group www.postgresql.org/developer | Oxford Semantic Technologies | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2012 | 2016 | 2017 | 1989 1989: Postgres, 1996: PostgreSQL | 2017 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | v24.4.1.2088-stable, May 2024 | 16.2, February 2024 | 6.0, Septermber 2022 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial free tier for a limited amount of database operations | Open Source Apache 2.0 | commercial | Open Source BSD | commercial | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | yes | no | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | C++ | C | C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | hosted | FreeBSD Linux macOS | hosted | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux macOS Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | yes | schema-free | yes | yes RDF schemas | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | no | Close to ANSI SQL (SQL/JSON + extensions) | no | yes standard with numerous extensions | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | RESTful HTTP API | 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 | ADO.NET JDBC native C library ODBC streaming API for large objects | RESTful HTTP API SPARQL 1.1 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | .Net ColdFusion Erlang Groovy Java JavaScript Perl PHP Python Ruby | 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 C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | C Java | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | no | yes | yes, Firebase Rules & Cloud Functions | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes by integration with AWS Lambda | no | yes, with Cloud Functions | 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. | Multi-source replication | Source-replica replication other methods possible by using 3rd party extensions | replication via a shared file system | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no may be implemented via Amazon Elastic MapReduce (Amazon EMR) | no | Using Cloud Dataflow | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency can be specified for read operations | Immediate Consistency | Immediate Consistency | Immediate Consistency | Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | no | no | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID ACID across one or more tables within a single AWS account and region | no | yes | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | 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 | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM) | 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. | fine grained access rights according to SQL-standard | Roles, resources, and access types | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Amazon DynamoDB | ClickHouse | Google Cloud Firestore | PostgreSQL | RDFox | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Conferences, events and webinars | Monitoring PostgreSQL with Redgate Monitor | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Recent citations in the news | How Heroku reduced their operational overhead by migrating their 30 TB self-managed database from Amazon EC2 to ... AWS announces Amazon DynamoDB zero-ETL integration with Amazon OpenSearch Service Simplify cross-account access control with Amazon DynamoDB using resource-based policies | Amazon Web Services Introducing configurable maximum throughput for Amazon DynamoDB on-demand | Amazon Web Services Bulk update Amazon DynamoDB tables with AWS Step Functions | Amazon Web Services 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 ... A 1000x Faster Database Solution: ClickHouse’s Aaron Katz From Open Source to SaaS: the Journey of ClickHouse Snowflake vs. BigQuery vs. ClickHouse: Mastering Cost-Effective Business Analytics 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 Cloud Firestore is now generally available Google launches Cloud Firestore, a new document database for app developers Firestore and Python | NoSQL on Google Cloud provided by Google News | AGEDB Technology Launches PGTS - PostgreSQL Tech-Support Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need PostgreSQL Security Flaws Let Attackers Execute Code Automatically Generate Types for Your PostgreSQL Database General availability: Microsoft Entra ID integration with Azure Cosmos DB for PostgreSQL | Azure updates provided by Google News | Use semantic reasoning to infer new facts from your RDF graph by integrating RDFox with Amazon Neptune | Amazon ... Eight interesting open-source graph databases Financial Crime Discovery using Amazon EKS and Graph Databases | Amazon Web Services Finding patterns with rules, using Knowledge Graphs and Semantic Reasoning | by Peter Crocker provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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