DBMS > Amazon DynamoDB vs. Couchbase vs. PostgreSQL vs. Vitess
System Properties Comparison Amazon DynamoDB vs. Couchbase vs. PostgreSQL vs. Vitess
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Name | Amazon DynamoDB Xexclude from comparison | Couchbase Originally called Membase Xexclude from comparison | PostgreSQL Xexclude from comparison | Vitess Xexclude from comparison | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Hosted, scalable database service by Amazon with the data stored in Amazons cloud | A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Scalable, distributed, cloud-native DBMS, extending MySQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store Key-value store | Document store | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Relational DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Key-value store originating from the former Membase product and supporting the Memcached protocol Spatial DBMS using the Geocouch extension Search engine Time Series DBMS Vector DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | Document store Spatial DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aws.amazon.com/dynamodb | www.couchbase.com | www.postgresql.org | vitess.io | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.aws.amazon.com/dynamodb | docs.couchbase.com | www.postgresql.org/docs | vitess.io/docs | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Amazon | Couchbase, Inc. | PostgreSQL Global Development Group www.postgresql.org/developer | The Linux Foundation, PlanetScale | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2012 | 2011 | 1989 1989: Postgres, 1996: PostgreSQL | 2013 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023 | 16.4, August 2024 | 15.0.2, December 2022 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial free tier for a limited amount of database operations | Open Source Business Source License (BSL 1.1); Commercial licenses also available | Open Source BSD | Open Source Apache Version 2.0, commercial licenses available | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | no | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | PostgreSQL Flex @ STACKIT offers managed PostgreSQL Instances with adjustable CPU, RAM, storage amount and speed and several extensions available, in enterprise grade to perfectly match all application requirements. All 100% GDPR-compliant. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C, C++, Go and Erlang | C | Go | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | Linux OS X Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Docker Linux macOS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | schema-free | 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. | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases | yes standard with numerous extensions | yes with proprietary extensions | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | RESTful HTTP API | CLI Client HTTP REST Kafka Connector Native language bindings for CRUD, Query, Search and Analytics APIs Spark Connector Spring Data | ADO.NET JDBC native C library ODBC streaming API for large objects | ADO.NET JDBC MySQL protocol ODBC | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net ColdFusion Erlang Groovy Java JavaScript Perl PHP Python Ruby | .Net C Go Java JavaScript Node.js Kotlin PHP Python Ruby Scala | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | Ada C C# C++ D Delphi Eiffel Erlang Haskell Java JavaScript (Node.js) Objective-C OCaml Perl PHP Python Ruby Scheme Tcl | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | Functions and timers in JavaScript and UDFs in Java, Python, SQL++ | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | yes proprietary syntax | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes by integration with AWS Lambda | yes via the TAP protocol | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Automatic Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes | Multi-source replication including cross data center replication Source-replica replication | Source-replica replication other methods possible by using 3rd party extensions | Multi-source replication Source-replica replication | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no may be implemented via Amazon Elastic MapReduce (Amazon EMR) | yes | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency can be specified for read operations | Eventual Consistency Immediate Consistency selectable on a per-operation basis | Immediate Consistency | Eventual Consistency across shards Immediate Consistency within a shard | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | yes | yes not for MyISAM storage engine | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | ACID | ACID | ACID at shard level | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes table locks or row locks depending on storage engine | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 Ephemeral buckets | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM) | User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control. | fine grained access rights according to SQL-standard | Users with fine-grained authorization concept no user groups or roles | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendorWe invite representatives of system vendors to contact us for updating and extending the system information, | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Amazon DynamoDB | Couchbase Originally called Membase | PostgreSQL | Vitess | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month | 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 | PASS Data Community Summit | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | How Samsung Cloud optimized Amazon DynamoDB costs | Amazon Web Services Migrating Uber's Ledger Data from DynamoDB to LedgerStore Join the preview of attribute-based access control for Amazon DynamoDB | Amazon Web Services Achieve near real-time analytics on Amazon DynamoDB with SingleStore Faster development with Amazon DynamoDB and Amazon Q Developer provided by Google News | Couchbase releases AI vector search and Capella Columnar on AWS Couchbase stock hits 52-week low at $14.1 amid market challenges Couchbase Announces New Features to Accelerate AI-Powered Adaptive Applications for Customers Couchbase Capella gets columnar support on AWS Couchbase (NASDAQ:BASE) Sets New 52-Week Low at $14.07 provided by Google News | YugabyteDB 2.19 gets new PostgreSQL-compatibility features YugabyteDB evolves into a distributed PostgreSQL database for apps that need resilience and scale Intel Demonstrates Up To 48% Improvement For AVX-512 Optimized PostgreSQL PostgreSQL in line for DuckDB-shaped boost in analytics arena PostgreSQL databases under attack provided by Google News | Deepthi Sigireddi on Distributed Database Architecture in the Cloud Native Era They scaled YouTube — now they’ll shard everyone with PlanetScale PlanetScale Unveils Distributed MySQL Database Service Based on Vitess PlanetScale offers undo button to reverse schema migration without losing data CNCF’s Vitess Scales MySQL with the Help of Kubernetes provided by Google News |
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