DBMS > Apache IoTDB vs. Fujitsu Enterprise Postgres vs. GraphDB vs. PostgreSQL vs. Sphinx
System Properties Comparison Apache IoTDB vs. Fujitsu Enterprise Postgres vs. GraphDB vs. PostgreSQL vs. Sphinx
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| Name | Apache IoTDB Xexclude from comparison | Fujitsu Enterprise Postgres Xexclude from comparison | GraphDB  former name: OWLIM Xexclude from comparison | PostgreSQL Xexclude from comparison | Sphinx Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink | Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features. | 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. | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Open source search engine for searching in data from different sources, e.g. relational databases | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Time Series DBMS | Relational DBMS | Graph DBMS RDF store | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Search engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | iotdb.apache.org | www.postgresql.fastware.com | www.ontotext.com | www.postgresql.org | sphinxsearch.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html | www.postgresql.fastware.com/product-manuals | graphdb.ontotext.com/documentation | www.postgresql.org/docs | sphinxsearch.com/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Social network pages |      | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Apache Software Foundation | PostgreSQL Global Development Group, Fujitsu Australia Software Technology | Ontotext | PostgreSQL Global Development Group www.postgresql.org/developer | Sphinx Technologies Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2018 | 2000 | 1989 1989: Postgres, 1996: PostgreSQL | 2001 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 1.1.0, April 2023 | Fujitsu Enterprise Postgres 14, January 2022 | 10.4, October 2023 | 16.3, May 2024 | 3.5.1, February 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | Open Source Apache Version 2.0 | commercial | commercial Some plugins of GraphDB Workbench are open sourced | Open Source BSD | Open Source GPL version 2, commercial licence available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | Java | C | Java | C | C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | All OS with a Java VM (>= 1.8) | Linux Windows | All OS with a Java VM Linux OS X Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | FreeBSD Linux NetBSD OS X Solaris Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes | yes | schema-free and OWL/RDFS-schema support; RDF shapes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 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 full-text index on all search fields | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SQL-like query language | yes | stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC | yes standard with numerous extensions | SQL-like query language (SphinxQL) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | JDBC Native API | ADO.NET JDBC native C library ODBC streaming API for large objects | GeoSPARQL GraphQL GraphQL Federation Java API JDBC RDF4J API RDFS RIO Sail API Sesame REST HTTP Protocol SPARQL 1.1 | ADO.NET JDBC native C library ODBC streaming API for large objects | Proprietary protocol | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | C C# C++ Go Java Python Scala | .Net C C++ Delphi Java JavaScript (Node.js) Perl PHP Python Tcl | .Net C# Clojure Java JavaScript (Node.js) PHP Python Ruby Scala | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | C++ unofficial client library Java Perl unofficial client libraryPHP Python Ruby unofficial client library | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | yes | user defined functions | well-defined plugin interfaces; JavaScript server-side extensibility | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes | yes | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | horizontal partitioning (by time range) + vertical partitioning (by deviceId) | partitioning by range, list and by hash | none | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding Partitioning is done manually, search queries against distributed index is supported | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas | Source-replica replication | Multi-source replication | Source-replica replication other methods possible by using 3rd party extensions | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | Integration with Hadoop and Spark | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Strong Consistency with Raft | Immediate Consistency | Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request) | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | yes | yes Constraint checking | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | ACID | ACID | ACID | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes, multi-version concurrency control (MVCC) | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes | yes The original contents of fields are not stored in the Sphinx index. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | yes | fine grained access rights according to SQL-standard | 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. | fine grained access rights according to SQL-standard | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Apache IoTDB | Fujitsu Enterprise Postgres | GraphDB former name: OWLIM | PostgreSQL | Sphinx | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | 100% compatible with community PostgreSQL » more | Ontotext GraphDB is a semantic database engine that allows organizations to build... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed... » more | GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | Transactional payments applications, reporting and mixed workloads. » more | Metadata enrichment and management, linked data publishing, semantic inferencing... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Key customers | GraphDB provides a platform for building next-generation AI and Knowledge Graph... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Market metrics | Over 30 years experience in database technology. Over 20 years in Postgres development... » more | GraphDB is the most utilized semantic triplestore for mission-critical enterprise... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | Core based licensing » more | GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| News | Integrating GraphDB with Relational Database Systems Understanding the Graph Center of Excellence Migrating From LPG to RDF Graph Model Case study: Policy Enforcement Automation With Semantics Okay, RAG… We Have a Problem | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Apache IoTDB | Fujitsu Enterprise Postgres | GraphDB former name: OWLIM | PostgreSQL | Sphinx | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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