DBMS > AllegroGraph vs. CouchDB vs. Faircom DB vs. Google Cloud Firestore vs. PostgreSQL
System Properties Comparison AllegroGraph vs. CouchDB vs. Faircom DB vs. Google Cloud Firestore vs. PostgreSQL
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| Name | AllegroGraph Xexclude from comparison | CouchDB  stands for "Cluster Of Unreliable Commodity Hardware" Xexclude from comparison | Faircom DB formerly c-treeACE Xexclude from comparison | Google Cloud Firestore Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | High performance, persistent RDF store with additional support for Graph DBMS | A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones. | Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs. | Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products. | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Document store with version 6.5 Graph DBMS RDF store Vector DBMS | Document store | Key-value store Relational DBMS | Document 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 | Spatial DBMS | Spatial DBMS using the Geocouch extension | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | allegrograph.com | couchdb.apache.org | www.faircom.com/products/faircom-db | firebase.google.com/products/firestore | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | franz.com/agraph/support/documentation/current/agraph-introduction.html | docs.couchdb.org/en/stable | docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html | firebase.google.com/docs/firestore | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Franz Inc. | Apache Software Foundation Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer | FairCom Corporation | PostgreSQL Global Development Group www.postgresql.org/developer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2004 | 2005 | 1979 | 2017 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 8.0, December 2023 | 3.3.3, December 2023 | V12, November 2020 | 16.3, May 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial Limited community edition free | Open Source Apache version 2 | commercial Restricted, free version available | commercial | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | no | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | Erlang | ANSI C, C++ | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux OS X Windows | Android BSD Linux OS X Solaris Windows | AIX FreeBSD HP-UX Linux NetBSD OS X QNX SCO Solaris VxWorks Windows easily portable to other OSs | hosted | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes RDF schemas | schema-free | schema free, schema optional, schema required, partial schema, | schema-free | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | no | yes, ANSI SQL Types, JSON, typed binary structures | 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 bulk load of XML files possible | no | no | no | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes via views | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SPARQL is used as query language | no | yes, ANSI SQL with proprietary extensions | no | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | RESTful HTTP API SPARQL | RESTful HTTP/JSON API | ADO.NET Direct SQL JDBC JPA ODBC RESTful HTTP/JSON API RESTful MQTT/JSON API RPC | Android gRPC (using protocol buffers) API iOS JavaScript API RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | C# Clojure Java Lisp Perl Python Ruby Scala | C C# ColdFusion Erlang Haskell Java JavaScript Lisp Lua Objective-C OCaml Perl PHP PL/SQL Python Ruby Smalltalk | .Net C C# C++ Java JavaScript (Node.js and browser) PHP Python Visual Basic | Go Java JavaScript JavaScript (Node.js) Objective-C Python | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | yes JavaScript or Common Lisp | View functions in JavaScript | yes .Net, JavaScript, C/C++ | yes, Firebase Rules & Cloud Functions | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes | yes | yes | yes, with Cloud Functions | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | with Federation | Sharding improved architecture with release 2.0 | File partitioning, horizontal partitioning, sharding Customizable business rules for table partitioning | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication Source-replica replication | Multi-source 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). | Multi-source replication | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no | yes | no | Using Cloud Dataflow | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency or Eventual Consistency depending on configuration | Eventual Consistency | Eventual Consistency Immediate Consistency Tunable consistency per server, database, table, and transaction | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | no | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no atomic operations within a single document possible | tunable from ACID to Eventually Consistent | yes | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes strategy: optimistic locking | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | Yes, tunable from durable to delayed durability to in-memory | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | no | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Users with fine-grained authorization concept, user roles and pluggable authentication | Access rights for users can be defined per database | Fine grained access rights according to SQL-standard with additional protections for files | Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth. | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| AllegroGraph | CouchDB stands for "Cluster Of Unreliable Commodity Hardware" | Faircom DB formerly c-treeACE | Google Cloud Firestore | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| News | How a Neuro-Symbolic AI Approach Can Improve Trust in AI Apps Can Neuro-Symbolic AI Solve AI’s Weaknesses? 100 Companies That Matter in KM – Franz Inc. Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar) What is Neuro-Symbolic AI? | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| AllegroGraph | CouchDB stands for "Cluster Of Unreliable Commodity Hardware" | Faircom DB formerly c-treeACE | Google Cloud Firestore | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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