DBMS > GraphDB vs. GridDB vs. Stardog vs. Vertica vs. YugabyteDB
System Properties Comparison GraphDB vs. GridDB vs. Stardog vs. Vertica vs. YugabyteDB
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| Name | GraphDB  former name: OWLIM Xexclude from comparison | GridDB Xexclude from comparison | Stardog Xexclude from comparison | Vertica OpenText™ Vertica™ Xexclude from comparison | YugabyteDB Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | 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 in-memory time series database optimized for IoT and Big Data | 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. | High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Graph DBMS RDF store | Time Series DBMS | Graph DBMS RDF store | Relational DBMS Column oriented | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Key-value store Relational DBMS | Spatial DBMS Time Series DBMS | Document store Wide column store | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | www.ontotext.com | griddb.net | www.stardog.com | www.vertica.com | www.yugabyte.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | graphdb.ontotext.com/documentation | docs.griddb.net | docs.stardog.com | vertica.com/documentation | docs.yugabyte.com github.com/yugabyte/yugabyte-db | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Developer | Ontotext | Toshiba Corporation | Stardog-Union | OpenText previously Micro Focus and Hewlett Packard | Yugabyte Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2000 | 2013 | 2010 | 2005 | 2017 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 10.4, October 2023 | 5.1, August 2022 | 7.3.0, May 2020 | 12.0.3, January 2023 | 2.19, September 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial Some plugins of GraphDB Workbench are open sourced | Open Source AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available | commercial 60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students | commercial Limited community edition free | Open Source Apache 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | no | no | no on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | Java | C++ | Java | C++ | C and C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | All OS with a Java VM Linux OS X Windows | Linux | Linux macOS Windows | Linux | Linux OS X | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free and OWL/RDFS-schema support; RDF shapes | yes | 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. | depending on used data model | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes numerical, string, blob, geometry, boolean, timestamp | 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 | no Import/export of XML data possible | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes | yes | yes supports real-time indexing in full-text and geospatial | No Indexes Required. Different internal optimization strategy, but same functionality included. | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC | SQL92, SQL-like TQL (Toshiba Query Language) | 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. | yes, PostgreSQL compatible | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | GeoSPARQL GraphQL GraphQL Federation Java API JDBC RDF4J API RDFS RIO Sail API Sesame REST HTTP Protocol SPARQL 1.1 | JDBC ODBC Proprietary protocol RESTful HTTP/JSON API | 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 | JDBC YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | .Net C# Clojure Java JavaScript (Node.js) PHP Python Ruby Scala | C C++ Go Java JavaScript (Node.js) Perl PHP Python Ruby | .Net Clojure Groovy Java JavaScript Python Ruby | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | C C# C++ Go Java JavaScript (Node.js) PHP Python Ruby Rust Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | well-defined plugin interfaces; JavaScript server-side extensibility | no | user defined functions and aggregates, HTTP Server extensions in Java | yes, PostgreSQL PL/pgSQL, with minor differences | yes sql, plpgsql, C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | no | yes | yes via event handlers | yes, called Custom Alerts | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | none | Sharding | none | horizontal partitioning, hierarchical partitioning | Hash and Range Sharding, row-level geo-partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication | Source-replica replication | Multi-source replication in HA-Cluster | Multi-source replication One, or more copies of data replicated across nodes, or object-store used for repository. | Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no | Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs | no | no Bi-directional Spark integration | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request) | Immediate consistency within container, eventual consistency across containers | Immediate Consistency in HA-Cluster | Immediate Consistency | Strong consistency on writes and tunable consistency on reads | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | yes Constraint checking | no | yes relationships in graphs | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID at container level | ACID | ACID | Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes | yes based on RocksDB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | no | 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. | Access rights for users can be defined per database | Access rights for users and roles | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| GraphDB former name: OWLIM | GridDB | Stardog | Vertica OpenText™ Vertica™ | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | Ontotext GraphDB is a semantic database engine that allows organizations to build... » more | GridDB is a highly scalable, in-memory time series database optimized for IoT and... » more | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » more | YugabyteDB is an open source distributed SQL database for cloud native transactional... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment... » more | 1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model... » more | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » more | PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS.... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | Metadata enrichment and management, linked data publishing, semantic inferencing... » more | Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system. » more | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | Systems of record and engagement for cloud native applications that require resilience,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Key customers | GraphDB provides a platform for building next-generation AI and Knowledge Graph... » more | Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki... » more | Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Market metrics | GraphDB is the most utilized semantic triplestore for mission-critical enterprise... » more | GitHub trending repository » more | 2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition... » more | Open Source license (AGPL v3 & Apache v2) Commercial license (subscription) » more | Cost-based models and subscription-based models are both available. One license is... » more | Apache 2.0 license for the database » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| News | Riding the Databricks Wave with Hybrid Knowledge Graphs Matching Skills and Candidates with Graph RAG A Triple Store RAG Retriever Integrating GraphDB with Relational Database Systems Understanding the Graph Center of Excellence | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| GraphDB former name: OWLIM | GridDB | Stardog | Vertica OpenText™ Vertica™ | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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