DBMS > eXtremeDB vs. GraphDB vs. Neo4j vs. Stardog vs. Vertica
System Properties Comparison eXtremeDB vs. GraphDB vs. Neo4j vs. Stardog vs. Vertica
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Name | eXtremeDB Xexclude from comparison | GraphDB former name: OWLIM Xexclude from comparison | Neo4j Xexclude from comparison | Stardog Xexclude from comparison | Vertica OpenText™ Vertica™ Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Natively in-memory DBMS with options for persistency, high-availability and clustering | 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 | Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization | Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS Time Series DBMS | Graph DBMS RDF store | Graph DBMS | Graph DBMS RDF store | Relational DBMS Column oriented | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Spatial DBMS Time Series DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | www.mcobject.com | www.ontotext.com | neo4j.com | www.stardog.com | www.vertica.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | www.mcobject.com/docs/extremedb.htm | graphdb.ontotext.com/documentation | neo4j.com/docs | docs.stardog.com | vertica.com/documentation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Developer | McObject | Ontotext | Neo4j, Inc. | Stardog-Union | OpenText previously Micro Focus and Hewlett Packard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2001 | 2000 | 2007 | 2010 | 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 8.2, 2021 | 10.4, October 2023 | 5.19, April 2024 | 7.3.0, May 2020 | 12.0.3, January 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | commercial Some plugins of GraphDB Workbench are open sourced | Open Source GPL version3, commercial licenses available | commercial 60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students | commercial Limited community edition free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C and C++ | Java | Java, Scala | Java | C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | AIX HP-UX Linux macOS Solaris Windows | 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 Windows | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | schema-free and OWL/RDFS-schema support; RDF shapes | schema-free and schema-optional | schema-free and OWL/RDFS-schema support | Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | 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 support of XML interfaces available | no | no Import/export of XML data possible | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 supports real-time indexing in full-text and geospatial | No Indexes Required. Different internal optimization strategy, but same functionality included. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes with the option: eXtremeSQL | stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC | no | Yes, compatible with all major SQL variants through dedicated BI/SQL Server | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | .NET Client API JDBC JNI ODBC Proprietary protocol RESTful HTTP API | 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 Mapper RESTful HTTP API Spring Data Neo4j TinkerPop 3 | GraphQL query language HTTP API Jena RDF API OWL RDF4J API Sesame REST HTTP Protocol SNARL SPARQL Spring Data Stardog Studio TinkerPop 3 | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net C C# C++ Java Lua Python Scala | .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 Clojure Groovy Java JavaScript Python Ruby | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | well-defined plugin interfaces; JavaScript server-side extensibility | yes User defined Procedures and Functions | user defined functions and aggregates, HTTP Server extensions in Java | yes, PostgreSQL PL/pgSQL, with minor differences | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes by defining events | no | yes via event handler | yes via event handlers | yes, called Custom Alerts | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | horizontal partitioning / sharding | none | yes using Neo4j Fabric | none | horizontal partitioning, hierarchical partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | Multi-source replication | Causal Clustering using Raft protocol available in in Enterprise Version only | Multi-source replication in HA-Cluster | Multi-source replication One, or more copies of data replicated across nodes, or object-store used for repository. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | no | no | no | no Bi-directional Spark integration | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | 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 in HA-Cluster | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes | yes Constraint checking | yes Relationships in graphs | yes relationships in graphs | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID | ACID | ACID | 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 | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | 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) | Access rights for users and roles | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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eXtremeDB | GraphDB former name: OWLIM | Neo4j | Stardog | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | Neo4j delivers graph technology that has been battle tested for performance and scale... » more | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » 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 | Neo4j is the market leader, graph database category creator, and the most widely... » more | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » 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 | Real-Time Recommendations Master Data Management Identity and Access Management Network... » more | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » 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 | Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers... » more | Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,... » 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 | Neo4j boasts the world's largest graph database ecosystem with more than 140 million... » 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 | GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial... » more | Cost-based models and subscription-based models are both available. One license is... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | 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 Scaling Understanding with the Help of Feedback Loops, Knowledge Graphs and NLP | This Week in Neo4j: Podcast, GraphRAG, GraphQL, Chatbot and more Neo4j Joins the Connect with Confluent Partner Program 10 Inspiring Projects to Spark Your NODES 2024 Presentation New Security Feature in Neo4j Aura: Customer Managed Keys Safeguarding Elections: How Graph Technology Powers Groundbreaking Research on Political Ads | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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eXtremeDB | GraphDB former name: OWLIM | Neo4j | Stardog | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Applying Graph Analytics to Game of Thrones MySQL, PostgreSQL and Redis are the winners of the March ranking The openCypher Project: Help Shape the SQL for Graphs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | eXtremeDB 8.4 Unveils Exciting New Features and Enhancements Latest embedded DBMS supports asymmetric multiprocessing systems McObject Delivers eXtremeDB 8.4 Improving Performance, Security, and Developer Productivity The Data in Hard Real-time SCADA Systems Lets Companies Do More with Less McObject’s new eXtremeDB Cluster provides distributed database solution for real-time apps provided by Google News | Ontotext's GraphDB Solution Now Available on the Microsoft Azure Marketplace Ontotext Unveils GraphDB 10.4 with Enhanced AWS Integration and ChatGPT Connector Ontotext's GraphDB 10 Brings Modern Data Architectures to the Mainstream with Better Resilience and Еаsier Operations Ontotext Platform 3.0 for Enterprise Knowledge Graphs Released Ontotext GraphDB 9.4 Enables SQL Access to Knowledge Graphs and Visual Mapping of Tabular Data to RDF provided by Google News | Neo4j Announces Collaboration with Microsoft to Advance GenAI and Data Solutions USA - English - India - English Neo4j CTO says new Graph Query Language standard will have 'massive ripple effects' Neo4j Is Planning IPO on Nasdaq, Largest Owner Greenbridge Says Neo4j Empowers Syracuse University with $250K Grant to Tackle Misinformation in 2024 Elections Leveraging Neo4j and Amazon Bedrock for an Explainable, Secure, and Connected Generative AI Solution | Amazon ... provided by Google News | Stonebraker Seeks to Invert the Computing Paradigm with DBOS How Embedded Analytics Help ISVs Overcome Challenges OpenText expands enterprise portfolio with AI and Micro Focus integrations Postgres pioneer Michael Stonebraker promises to upend the database once more OpenText integrates Micro Focus tech through Cloud Editions 23.3 provided by Google News |
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