DBMS > Amazon DynamoDB vs. Couchbase vs. Greenplum vs. PostgreSQL vs. Trafodion
System Properties Comparison Amazon DynamoDB vs. Couchbase vs. Greenplum vs. PostgreSQL vs. Trafodion
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| Name | Amazon DynamoDB Xexclude from comparison | Couchbase  Originally called Membase Xexclude from comparison | Greenplum Xexclude from comparison | PostgreSQL Xexclude from comparison | Trafodion Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image. | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Transactional SQL-on-Hadoop DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Document store Key-value store | Document 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. | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Key-value store originating from the former Membase product and supporting the Memcached protocol Spatial DBMS using the Geocouch extensionSearch engine Time Series DBMS Vector DBMS | Document store Spatial DBMS | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | aws.amazon.com/dynamodb | www.couchbase.com | greenplum.org | www.postgresql.org | trafodion.apache.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.aws.amazon.com/dynamodb | docs.couchbase.com | docs.greenplum.org | www.postgresql.org/docs | trafodion.apache.org/documentation.html | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Amazon | Couchbase, Inc. | Pivotal Software Inc. | PostgreSQL Global Development Group www.postgresql.org/developer | Apache Software Foundation, originally developed by HP | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2012 | 2011 | 2005 | 1989 1989: Postgres, 1996: PostgreSQL | 2014 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023 | 7.0.0, September 2023 | 16.3, May 2024 | 2.3.0, February 2019 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 Apache 2.0 | Open Source BSD | Open Source Apache 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | C, C++, Go and Erlang | C | C++, Java | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | hosted | Linux OS X Windows | Linux | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | schema-free | yes | 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. | yes since Version 4.2 | yes specific XML-type available, but no XML query functionality. | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | no | SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases | yes | yes standard with numerous extensions | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | JDBC ODBC | ADO.NET JDBC native C library ODBC streaming API for large objects | ADO.NET JDBC ODBC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | .Net ColdFusion Erlang Groovy Java JavaScript Perl PHP Python Ruby | .Net C Go Java JavaScript Node.jsKotlin PHP Python Ruby Scala | C Java Perl Python R | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | All languages supporting JDBC/ODBC/ADO.Net | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | no | Functions and timers in JavaScript and UDFs in Java, Python, SQL++ | yes | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | Java Stored Procedures | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes by integration with AWS Lambda | yes via the TAP protocol | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding | Automatic Sharding | 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 | Source-replica replication other methods possible by using 3rd party extensions | yes, via HBase | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no may be implemented via Amazon Elastic MapReduce (Amazon EMR) | yes | yes | no | yes via user defined functions and HBase | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | no | yes | yes | 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 | ACID | ACID | ACID | 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 Ephemeral buckets | no | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Amazon DynamoDB | Couchbase Originally called Membase | Greenplum | PostgreSQL | Trafodion | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Recent citations in the news | 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 Simplify private connectivity to Amazon DynamoDB with AWS PrivateLink | Amazon Web Services Introducing configurable maximum throughput for Amazon DynamoDB on-demand | Amazon Web Services A new and improved AWS CDK construct for Amazon DynamoDB tables | Amazon Web Services provided by Google News | Database company Couchbase cruises to another solid earnings and revenue beat A Closer Look at 9 Analyst Recommendations For Couchbase Couchbase, Inc. (NASDAQ:BASE) Shares Slammed 29% But Getting In Cheap Might Be Difficult Regardless Couchbase (NASDAQ:BASE) Posts Better-Than-Expected Sales In Q1, Next Quarter's Growth Looks Optimistic Couchbase, Inc. (BASE) Tops Q1 EPS by 5c; offers outlook provided by Google News | 1. Introducing the Greenplum Database - Data Warehousing with Greenplum [Book] VMware Greenplum on AWS: Parallel Postgres for Enterprise Analytics at Scale | Amazon Web Services RSA: EMC integrates Hadoop with Greenplum database Greenplum 6 ventures outside the analytic box | ZDNET Greenplum 6 review: Jack of all trades, master of some provided by Google News | Build a FedRAMP compliant generative AI-powered chatbot using Amazon Aurora Machine Learning and Amazon ... PostgreSQL Tutorial: Definition, Commands, & Features How To Schedule PostgreSQL Backups With GitHub Actions Raise the bar on AI-powered app development with Azure Database for PostgreSQL How to implement a better like, views, comment counters in PostgreSQL? provided by Google News | Evaluating HTAP Databases for Machine Learning Applications Low-latency, distributed database architectures are critical for emerging fog applications provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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