DBMS > Faircom DB vs. Greenplum vs. MarkLogic vs. openGauss vs. PostgreSQL
System Properties Comparison Faircom DB vs. Greenplum vs. MarkLogic vs. openGauss vs. PostgreSQL
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Name | Faircom DB formerly c-treeACE Xexclude from comparison | Greenplum Xexclude from comparison | MarkLogic Xexclude from comparison | openGauss Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | 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 | An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Key-value store Relational DBMS | Relational DBMS | Document store Native XML DBMS RDF store as of version 7 Search engine | Relational DBMS | 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 | Document store Spatial DBMS | Document store Spatial DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | www.faircom.com/products/faircom-db | greenplum.org | www.marklogic.com | gitee.com/opengauss opengauss.org | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html | docs.greenplum.org | docs.marklogic.com | docs.opengauss.org/en gitee.com/opengauss/docs | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | FairCom Corporation | Pivotal Software Inc. | MarkLogic Corp. | Huawei and openGauss community | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 1979 | 2005 | 2001 | 2019 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | V12, November 2020 | 7.0.0, September 2023 | 11.0, December 2022 | 3.0, March 2022 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial Restricted, free version available | Open Source Apache 2.0 | commercial restricted free version is available | Open Source | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | ANSI C, C++ | C++ | C, C++, Java | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | AIX FreeBSD HP-UX Linux NetBSD OS X QNX SCO Solaris VxWorks Windows easily portable to other OSs | Linux | Linux OS X Windows | Linux | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema free, schema optional, schema required, partial schema, | yes | schema-free Schema can be enforced | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes, ANSI SQL Types, JSON, typed binary structures | 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 | yes since Version 4.2 | yes | no | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes, ANSI SQL with proprietary extensions | yes | yes SQL92 | ANSI SQL 2011 | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | 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 9 RESTful HTTP API SPARQL WebDAV XDBC XQuery XSLT | JDBC ODBC | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .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 | C C++ Java | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes .Net, JavaScript, C/C++ | yes | yes via XQuery or JavaScript | yes | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | File partitioning, horizontal partitioning, sharding Customizable business rules for table partitioning | Sharding | Sharding | horizontal partitioning (by range, list and hash) | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | 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 | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | yes | yes via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency Tunable consistency per server, database, table, and transaction | Immediate Consistency | Immediate Consistency | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes | yes | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | tunable from ACID to Eventually Consistent | ACID | ACID can act as a resource manager in an XA/JTA transaction | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | Yes, tunable from durable to delayed durability to in-memory | 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, with Range Indexes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts 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 | Access rights for users, groups and roles according to SQL-standard | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Faircom DB formerly c-treeACE | Greenplum | MarkLogic | openGauss | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | 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 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 openGauss Open Source Community Officially Launch The openGauss powers database industry forward through innovation Engineering Students from Thammasat Win 2 'Huawei ICT' Awards to Represent Thailand in Asia-Pacific Competition. Huawei and OrangePi launches Raspberry Pi alternative with mystery CPU and AI chip Huawei unveils OrangePi Kunpeng Pro development board provided by Google News Enterprise DB begins rolling AI features into PostgreSQL EDB unveils EDB Postgres AI Building a CRUD App with Node.js, PostgreSQL, and Prisma Deep PostgreSQL Thoughts: Valuing Currency Nutanix partners with EDB to fit database service for AI – Blocks and Files provided by Google News |
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