DBMS > Amazon DynamoDB vs. ClickHouse vs. Heroic vs. Microsoft Azure Table Storage vs. PostgreSQL
System Properties Comparison Amazon DynamoDB vs. ClickHouse vs. Heroic vs. Microsoft Azure Table Storage vs. PostgreSQL
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| Name | Amazon DynamoDB Xexclude from comparison | ClickHouse Xexclude from comparison | Heroic Xexclude from comparison | Microsoft Azure Table Storage Xexclude from comparison | PostgreSQL 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. | Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch | A Wide Column Store for rapid development using massive semi-structured datasets | Widely used open source RDBMS  Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Document store Key-value store | Relational DBMS | Time Series DBMS | 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 | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | aws.amazon.com/dynamodb | clickhouse.com | github.com/spotify/heroic | azure.microsoft.com/en-us/services/storage/tables | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.aws.amazon.com/dynamodb | clickhouse.com/docs | spotify.github.io/heroic | www.postgresql.org/docs | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Amazon | Clickhouse Inc. | Spotify | Microsoft | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2012 | 2016 | 2014 | 2012 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | v24.4.1.2088-stable, May 2024 | 16.3, May 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial free tier for a limited amount of database operations | Open Source Apache 2.0 | Open Source Apache 2.0 | commercial | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | yes | no | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | C++ | Java | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | hosted | FreeBSD Linux macOS | hosted | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | yes | schema-free | schema-free | 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 | yes specific XML-type available, but no XML query functionality. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | yes via Elasticsearch | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | no | Close to ANSI SQL (SQL/JSON + extensions) | no | no | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | RESTful HTTP API | gRPC HTTP REST JDBC MySQL wire protocol ODBC PostgreSQL wire protocol Proprietary protocol | HQL (Heroic Query Language, a JSON-based language) HTTP API | RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | .Net C# C++ Java JavaScript (Node.js) PHP Python Ruby | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | no | yes | no | no | 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 | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding | key based and custom | Sharding | Sharding Implicit feature of the cloud service | 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. | yes | yes implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no may be implemented via Amazon Elastic MapReduce (Amazon EMR) | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency can be specified for read operations | Immediate Consistency | Eventual Consistency Immediate Consistency | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | 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 | no | optimistic locking | 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 | no | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 based on private key authentication or shared access signatures | 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 | 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 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 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 Instaclustr: Fully Hosted & Managed PostgreSQL » 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 Redgate webinars: A series of key topics for new PostgreSQL users. » more SharePlex is the reliable and affordable data replication solution for PostgreSQL migrations, high availability and more. » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Amazon DynamoDB | ClickHouse | Heroic | Microsoft Azure Table Storage | 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 Freecharge lowered their identity management system cost and improved scaling by switching to Amazon DynamoDB ... Migrating Uber's Ledger Data from DynamoDB to LedgerStore Zendesk Moves from DynamoDB to MySQL and S3 to Save over 80% in Costs Introducing configurable maximum throughput for Amazon DynamoDB on-demand | Amazon Web Services Using the circuit-breaker pattern with AWS Lambda extensions and Amazon DynamoDB | Amazon Web Services provided by Google News Ubuntu 24.04 + Linux 6.9 Intel & AMD Server Performance 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 ClickHouse Announces Launch of ClickPipes provided by Google News Review: Google Bigtable scales with ease provided by Google News Working with Azure to Use and Manage Data Lakes Azure Cosmos DB Data Migration tool imports from Azure Table storage | Azure updates How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB How to use Azure Table storage in .Net How to write data to Azure Table Store with an Azure Function provided by Google News Enterprise DB begins rolling AI features into PostgreSQL How LeadSquared accelerated chatbot deployments with generative AI using Amazon Bedrock and Amazon Aurora ... Nutanix partners with EDB to fit database service for AI – Blocks and Files How to Import CSV Data Into PostgreSQL Using Spring Boot Batch EDB unveils EDB Postgres AI provided by Google News | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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