DBMS > eXtremeDB vs. FatDB vs. GraphDB vs. MongoDB vs. PostgreSQL
System Properties Comparison eXtremeDB vs. FatDB vs. GraphDB vs. MongoDB vs. PostgreSQL
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Name | eXtremeDB Xexclude from comparison | FatDB Xexclude from comparison | GraphDB former name: OWLIM Xexclude from comparison | MongoDB Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Natively in-memory DBMS with options for persistency, high-availability and clustering | A .NET NoSQL DBMS that can integrate with and extend SQL Server. | Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL. | One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS Time Series DBMS | Document store Key-value store | Graph DBMS RDF 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Spatial DBMS Search engine integrated Lucene index, currently in MongoDB Atlas only. Time Series DBMS Time Series Collections introduced in Release 5.0 Vector DBMS currently available in the MongoDB Atlas cloud service only | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | www.mcobject.com | www.ontotext.com | www.mongodb.com | www.postgresql.org | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | www.mcobject.com/docs/extremedb.htm | graphdb.ontotext.com/documentation | www.mongodb.com/docs/manual | www.postgresql.org/docs | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Developer | McObject | FatCloud | Ontotext | MongoDB, Inc | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2001 | 2012 | 2000 | 2009 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 8.2, 2021 | 10.4, October 2023 | 6.0.7, June 2023 | 16.2, February 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | commercial | commercial Some plugins of GraphDB Workbench are open sourced | Open Source MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available. | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no MongoDB available as DBaaS (MongoDB Atlas) | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more. | Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C and C++ | C# | Java | C++ | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | AIX HP-UX Linux macOS Solaris Windows | Windows | All OS with a Java VM Linux OS X Windows | Linux OS X Solaris Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | schema-free | schema-free and OWL/RDFS-schema support; RDF shapes | schema-free Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema. | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | yes string, integer, double, decimal, boolean, date, object_id, geospatial | 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 support of XML interfaces available | no | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes with the option: eXtremeSQL | no Via inetgration in SQL Server | stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC | Read-only SQL queries via the MongoDB Atlas SQL Interface | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | .NET Client API JDBC JNI ODBC Proprietary protocol RESTful HTTP API | .NET Client API LINQ RESTful HTTP API RPC Windows WCF Bindings | GeoSPARQL GraphQL GraphQL Federation Java API JDBC RDF4J API RDFS RIO Sail API Sesame REST HTTP Protocol SPARQL 1.1 | GraphQL HTTP REST Prisma proprietary protocol using JSON | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net C C# C++ Java Lua Python Scala | C# | .Net C# Clojure Java JavaScript (Node.js) PHP Python Ruby Scala | Actionscript unofficial driver C C# C++ Clojure unofficial driver ColdFusion unofficial driver D unofficial driver Dart unofficial driver Delphi unofficial driver Erlang Go Groovy unofficial driver Haskell Java JavaScript Kotlin Lisp unofficial driver Lua unofficial driver MatLab unofficial driver Perl PHP PowerShell unofficial driver Prolog unofficial driver Python R unofficial driver Ruby Rust Scala Smalltalk unofficial driver Swift | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | yes via applications | well-defined plugin interfaces; JavaScript server-side extensibility | JavaScript | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes by defining events | yes via applications | no | yes in MongoDB Atlas only | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | horizontal partitioning / sharding | Sharding | none | Sharding Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime. | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Active Replication Fabric™ for IoT Multi-source replication by means of eXtremeDB Cluster option Source-replica replication by means of eXtremeDB High Availability option | selectable replication factor | Multi-source replication | Multi-Source deployments with MongoDB Atlas Global Clusters 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 | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Eventual Consistency Immediate Consistency | Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request) | Eventual Consistency can be individually decided for each read operation Immediate Consistency default behaviour | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes | no | yes Constraint checking | no typically not used, however similar functionality with DBRef possible | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no | ACID | Multi-document ACID Transactions with snapshot isolation | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes Optimistic (MVCC) and pessimistic (locking) strategies available | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes optional, enabled by default | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes In-memory storage engine introduced with MongoDB version 3.2 | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | no Can implement custom security layer via applications | Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on. | Access rights for users and roles | fine grained access rights according to SQL-standard | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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eXtremeDB | FatDB | GraphDB former name: OWLIM | MongoDB | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small... » more | Ontotext GraphDB is a semantic database engine that allows organizations to build... » more | MongoDB provides an integrated suite of cloud database and data services to accelerate... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | eXtremeDB databases can be modeled relationally or as objects and can utilize SQL... » more | GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment... » more | Built around the flexible document data model and unified API, MongoDB is a developer... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,... » more | Metadata enrichment and management, linked data publishing, semantic inferencing... » more | AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,... » more | GraphDB provides a platform for building next-generation AI and Knowledge Graph... » more | ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | With hundreds of customers and over 30 million devices/applications using the product... » more | GraphDB is the most utilized semantic triplestore for mission-critical enterprise... » more | Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | For server use cases, there is a simple per-server license irrespective of the number... » more | GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition... » more | MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Case study: Policy Enforcement Automation With Semantics Okay, RAG… We Have a Problem Scaling Understanding with the Help of Feedback Loops, Knowledge Graphs and NLP How Knowledge Graphs Power Data Mesh and Data Fabric Building Smarter Financial Services: The Role of Semantic Technologies, Knowledge Graphs and Generative AI | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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eXtremeDB | FatDB | GraphDB former name: OWLIM | MongoDB | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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