DBMS > Faircom DB vs. GraphDB vs. Neo4j vs. Postgres-XL vs. PostgreSQL
System Properties Comparison Faircom DB vs. GraphDB vs. Neo4j vs. Postgres-XL vs. PostgreSQL
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| Name | Faircom DB  formerly c-treeACE Xexclude from comparison | GraphDB former name: OWLIM Xexclude from comparison | Neo4j Xexclude from comparison | Postgres-XL 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. | 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. | Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings | Based on PostgreSQL enhanced with MPP and write-scale-out cluster features | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Key-value store Relational DBMS | Graph DBMS RDF store | Graph DBMS | 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 Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | www.faircom.com/products/faircom-db | www.ontotext.com | neo4j.com | www.postgres-xl.org | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html | graphdb.ontotext.com/documentation | neo4j.com/docs | www.postgres-xl.org/documentation | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Social network pages |      | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | FairCom Corporation | Ontotext | Neo4j, Inc. | PostgreSQL Global Development Group www.postgresql.org/developer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 1979 | 2000 | 2007 | 2014 since 2012, originally named StormDB | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | V13, July 2024 | 10.4, October 2023 | 5.23, August 2024 | 10 R1, October 2018 | 16.4, August 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial Restricted, free version available | commercial Some plugins of GraphDB Workbench are open sourced | Open Source GPL version3, commercial licenses available | Open Source Mozilla public license | 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. | Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers. | PostgreSQL Flex @ STACKIT offers managed PostgreSQL Instances with adjustable CPU, RAM, storage amount and speed and several extensions available, in enterprise grade to perfectly match all application requirements. All 100% GDPR-compliant. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | ANSI C, C++ | Java | Java, Scala | C | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | AIX FreeBSD HP-UX Linux NetBSD OS X QNX SCO Solaris VxWorks Windows easily portable to other OSs | All OS with a Java VM Linux OS X Windows | Linux Can also be used server-less as embedded Java database. OS X Solaris Windows | Linux macOS | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema free, schema optional, schema required, partial schema, | schema-free and OWL/RDFS-schema support; RDF shapes | schema-free and schema-optional | 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 | no | yes XML type, but no XML query functionality | yes specific XML-type available, but no XML query functionality. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes | yes pluggable indexing subsystem, by default Apache Lucene | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | yes, ANSI SQL with proprietary extensions | stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC | no | yes distributed, parallel query execution | 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 | GeoSPARQL GraphQL GraphQL Federation Java API JDBC RDF4J API RDFS RIO Sail API Sesame REST HTTP Protocol SPARQL 1.1 | Bolt protocol Cypher query language Java API Neo4j-OGM Object Graph MapperRESTful HTTP API Spring Data Neo4j TinkerPop 3 | ADO.NET JDBC native C library ODBC streaming API for large objects | 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 | .Net C# Clojure Java JavaScript (Node.js) PHP Python Ruby Scala | .Net Clojure Elixir Go Groovy Haskell Java JavaScript Perl PHP Python Ruby Scala | .Net C C++ Delphi Erlang Java JavaScript (Node.js) Perl PHP Python Tcl | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | yes .Net, JavaScript, C/C++ | well-defined plugin interfaces; JavaScript server-side extensibility | yes User defined Procedures and Functions | user defined functions | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes | no | yes via event handler | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | File partitioning, horizontal partitioning, sharding Customizable business rules for table partitioning | none | yes using Neo4j Fabric | horizontal partitioning | 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). | Multi-source replication | Causal Clustering using Raft protocol available in in Enterprise Version only | Source-replica replication other methods possible by using 3rd party extensions | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no | no | no | 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, Eventual consistency (configurable in cluster mode per master or individual client request) | Causal and Eventual Consistency configurable in Causal Cluster setup Immediate Consistency in stand-alone mode | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | yes | yes Constraint checking | yes Relationships in graphs | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | tunable from ACID to Eventually Consistent | ACID | ACID | ACID MVCC | 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 | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Fine grained access rights according to SQL-standard with additional protections for files | 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. | Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos) | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Faircom DB formerly c-treeACE | GraphDB former name: OWLIM | Neo4j | Postgres-XL | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | Ontotext GraphDB is a semantic database engine that allows organizations to build... » more | Neo4j delivers graph technology that has been battle tested for performance and scale... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment... » more | Neo4j is the market leader, graph database category creator, and the most widely... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | Metadata enrichment and management, linked data publishing, semantic inferencing... » more | Real-Time Recommendations Master Data Management Identity and Access Management Network... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Key customers | GraphDB provides a platform for building next-generation AI and Knowledge Graph... » more | Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Market metrics | GraphDB is the most utilized semantic triplestore for mission-critical enterprise... » more | Neo4j boasts the world's largest graph database ecosystem with more than 140 million... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition... » more | GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| News | GraphDB in Action: Using Semantics To Push The Envelope Of Software Engineering, Machine Learning, and E-Health Domains Accelerating End-to-end Knowledge Graph Solutions with Ontotext’s LinkedLifeData Inventory: The Case of Target Discovery Using Entity Linking to Turn Your Graph into a Knowledge Graph Considerations to Creating a Graph Center of Excellence: 5 Elements to Ensure Success The Power of Knowledge Graphs – A Chat with Perfect Memory and Ontotext | The Ethics of Generative AI: Understanding the Principles and Risks GraphSummit Europe 2024: Actionable Insights From Industry Leaders and Innovators This Week in Neo4j: Knowledge Graph, Data Loading, Olympics, CSV and more Neo4j Expands Cloud Database Capabilities to Power Enterprise-Scale Graph Deployments This Week in Neo4j: NODES 2024, GraphRAG, Graph Data, Knowledge Graph and more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Faircom DB formerly c-treeACE | GraphDB former name: OWLIM | Neo4j | Postgres-XL | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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