DBMS > Couchbase vs. Faircom DB vs. Greenplum vs. MarkLogic vs. PostgreSQL
System Properties Comparison Couchbase vs. Faircom DB vs. Greenplum vs. MarkLogic vs. PostgreSQL
| Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Name | Couchbase  Originally called Membase Xexclude from comparison | Faircom DB formerly c-treeACE Xexclude from comparison | Greenplum Xexclude from comparison | MarkLogic Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database | Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs. | 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. | Operational and transactional Enterprise NoSQL database | 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 | Relational DBMS | Document store Native XML DBMS RDF store as of version 7Search engine | 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 | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|
|
|
|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Website | www.couchbase.com | www.faircom.com/products/faircom-db | greenplum.org | www.marklogic.com | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.couchbase.com | docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html | docs.greenplum.org | docs.marklogic.com | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Couchbase, Inc. | FairCom Corporation | Pivotal Software Inc. | MarkLogic Corp. | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2011 | 1979 | 2005 | 2001 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023 | V12, November 2020 | 7.0.0, September 2023 | 11.0, December 2022 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | Open Source Business Source License (BSL 1.1); Commercial licenses also available | commercial Restricted, free version available | Open Source Apache 2.0 | commercial restricted free version is available | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. |
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | C, C++, Go and Erlang | ANSI C, C++ | C++ | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux OS X Windows | AIX FreeBSD HP-UX Linux NetBSD OS X QNX SCO Solaris VxWorks Windows easily portable to other OSs | Linux | Linux OS X Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | schema free, schema optional, schema required, partial schema, | yes | schema-free Schema can be enforced | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes, ANSI SQL Types, JSON, typed binary structures | 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 | yes since Version 4.2 | yes | yes specific XML-type available, but no XML query functionality. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases | yes, ANSI SQL with proprietary extensions | yes | yes SQL92 | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | CLI Client HTTP REST Kafka Connector Native language bindings for CRUD, Query, Search and Analytics APIs Spark Connector Spring Data | ADO.NET Direct SQL JDBC JPA ODBC RESTful HTTP/JSON API RESTful MQTT/JSON API RPC | JDBC ODBC | Java API Node.js Client API ODBC proprietary Optic API Proprietary Query API, introduced with version 9RESTful HTTP API SPARQL WebDAV XDBC XQuery XSLT | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | .Net C Go Java JavaScript Node.jsKotlin PHP Python Ruby Scala | .Net C C# C++ Java JavaScript (Node.js and browser) PHP Python Visual Basic | C Java Perl Python R | C C# C++ Java JavaScript (Node.js) Perl PHP Python Ruby | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | Functions and timers in JavaScript and UDFs in Java, Python, SQL++ | yes .Net, JavaScript, C/C++ | yes | yes via XQuery or JavaScript | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes via the TAP protocol | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Automatic Sharding | File partitioning, horizontal partitioning, sharding Customizable business rules for table partitioning | Sharding | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication including cross data center replication Source-replica replication | yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution). | Source-replica replication | yes | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | yes | no | yes | yes via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency selectable on a per-operation basis | Eventual Consistency Immediate Consistency Tunable consistency per server, database, table, and transaction | Immediate Consistency | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | yes | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | tunable from ACID to Eventually Consistent | ACID | ACID can act as a resource manager in an XA/JTA transaction | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | Yes, tunable from durable to delayed durability to in-memory | 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 | yes | no | yes, with Range Indexes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control. | Fine grained access rights according to SQL-standard with additional protections for files | fine grained access rights according to SQL-standard | Role-based access control at the document and subdocument levels | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendorWe invite representatives of system vendors to contact us for updating and extending the system information, | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Related products and services | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 3rd parties | CData: Connect to Big Data & NoSQL through standard Drivers. » more | Navicat for PostgreSQL is an easy-to-use graphical tool for PostgreSQL database development. » more SharePlex is the reliable and affordable data replication solution for PostgreSQL migrations, high availability and more. » 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 pgDash: In-Depth PostgreSQL Monitoring. » more Navicat Monitor is a safe, simple and agentless remote server monitoring tool for PostgreSQL and many other database management systems. » 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 Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools. » more Redgate webinars: A series of key topics for new PostgreSQL users. » 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
We invite representatives of vendors of related products to contact us for presenting information about their offerings here. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Couchbase Originally called Membase | Faircom DB formerly c-treeACE | Greenplum | MarkLogic | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | 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 Monitoring PostgreSQL with Redgate Monitor 11 Analysts Have This To Say About Couchbase UBS Starts Couchbase Inc (BASE) at Neutral Couchbase (NASDAQ:BASE) Earns Neutral Rating from Analysts at UBS Group UBS Neutral on Couchbase stock citing Capella's growth potential Couchbase Announces New Features to Accelerate AI-Powered Adaptive Applications for Customers provided by Google News FairCom kicks off new era of database technology USA - English provided by Google News VMware Greenplum on AWS: Parallel Postgres for Enterprise Analytics at Scale | Amazon Web Services 1. Introducing the Greenplum Database - Data Warehousing with Greenplum [Book] RSA: EMC integrates Hadoop with Greenplum database Greenplum 6 ventures outside the analytic box Greenplum 6 review: Jack of all trades, master of some provided by Google News Progress (PRGS) Set to Buy MarkLogic, Guides Upbeat Q4 Results MarkLogic “The NoSQL Database”. In the MarkLogic Query Console, you can… | by Abhay Srivastava | Apr, 2024 Database Platform to Simplify Complex Data | Progress Marklogic ABN AMRO Moves Progress-Powered Credit Store App to Azure Cloud; Achieves 40% Faster Data Processing, Lower ... AI can make logistics data as valuable as intelligence or operational data for mission success provided by Google News Deep PostgreSQL Thoughts: Valuing Currency At Build, Microsoft Fabric, PostgreSQL and Cosmos DB get AI enhancements Nutanix partners with EDB to fit database service for AI – Blocks and Files How to Import CSV Data Into PostgreSQL Using Spring Boot Batch Nutanix and EDB enhance PostgreSQL for enterprise apps provided by Google News | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Share this page
