DBMS > GraphDB vs. Microsoft Azure SQL Database vs. Tarantool vs. TypeDB vs. Vertica
System Properties Comparison GraphDB vs. Microsoft Azure SQL Database vs. Tarantool vs. TypeDB vs. Vertica
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Name | GraphDB former name: OWLIM Xexclude from comparison | Microsoft Azure SQL Database formerly SQL Azure Xexclude from comparison | Tarantool Xexclude from comparison | TypeDB formerly named Grakn Xexclude from comparison | Vertica OpenText™ Vertica™ 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. | Database as a Service offering with high compatibility to Microsoft SQL Server | In-memory computing platform with a flexible data schema for efficiently building high-performance applications | TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language | 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 | Graph DBMS RDF store | Relational DBMS | Document store Key-value store Relational DBMS | Graph DBMS Relational DBMS Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies. | Relational DBMS Column oriented | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store Graph DBMS Spatial DBMS | Spatial DBMS with Tarantool/GIS extension | Spatial DBMS Time Series DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | www.ontotext.com | azure.microsoft.com/en-us/products/azure-sql/database | www.tarantool.io | typedb.com | www.vertica.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | graphdb.ontotext.com/documentation | docs.microsoft.com/en-us/azure/azure-sql | www.tarantool.io/en/doc | typedb.com/docs | vertica.com/documentation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Social network pages | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Ontotext | Microsoft | VK | Vaticle | OpenText previously Micro Focus and Hewlett Packard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2000 | 2010 | 2008 | 2016 | 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 10.4, October 2023 | V12 | 2.10.0, May 2022 | 2.26.3, January 2024 | 12.0.3, January 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial Some plugins of GraphDB Workbench are open sourced | commercial | Open Source BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise | Open Source GPL Version 3, commercial licenses available | commercial Limited community edition free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | yes | 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. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | Java | C++ | C and C++ | Java | C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | All OS with a Java VM Linux OS X Windows | hosted | BSD Linux macOS | Linux OS X Windows | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free and OWL/RDFS-schema support; RDF shapes | yes | Flexible data schema: relational definition for tables with ability to store json-like documents in columns | yes | 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 | string, double, decimal, uuid, integer, blob, boolean, datetime | 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 | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes | yes | yes | yes | No Indexes Required. Different internal optimization strategy, but same functionality included. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC | yes | Full-featured ANSI SQL support | no | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | ADO.NET JDBC ODBC | Open binary protocol | gRPC protocol TypeDB Console (shell) TypeDB Studio (Visualisation software- previously TypeDB Workbase) | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net C# Clojure Java JavaScript (Node.js) PHP Python Ruby Scala | .Net C# Java JavaScript (Node.js) PHP Python Ruby | C C# C++ Erlang Go Java JavaScript Lua Perl PHP Python Rust | All JVM based languages Groovy Java JavaScript (Node.js) Python Scala | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | well-defined plugin interfaces; JavaScript server-side extensibility | Transact SQL | Lua, C and SQL stored procedures | no | yes, PostgreSQL PL/pgSQL, with minor differences | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes | yes, before/after data modification events, on replication events, client session events | no | yes, called Custom Alerts | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | none | Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime. | Sharding by using Cassandra | horizontal partitioning, hierarchical partitioning | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication | yes, with always 3 replicas available | Asynchronous replication with multi-master option Configurable replication topology (full-mesh, chain, star) Synchronous quorum replication (with Raft) | Multi-source replication by using Cassandra | 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 | yes by using Apache Kafka and Apache Zookeeper | no Bi-directional Spark integration | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | Casual consistency across sharding partitions Eventual consistency within replicaset partition when using asyncronous replication Immediate Consistency within single instance Sequential consistency including linearizable read within replicaset partition when using Raft | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes Constraint checking | yes | yes | no substituted by the relationship feature | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID | ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes, cooperative multitasking | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes, write ahead logging | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes, full featured in-memory storage engine with persistence | 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. | fine grained access rights according to SQL-standard | Access Control Lists Mutual TLS authentication for Tarantol Enterprise Password based authentication Role-based access control (RBAC) and LDAP for Tarantol Enterprise Users and Roles | yes at REST API level; other APIs in progress | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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GraphDB former name: OWLIM | Microsoft Azure SQL Database formerly SQL Azure | Tarantool | TypeDB formerly named Grakn | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Ontotext GraphDB is a semantic database engine that allows organizations to build... » more | TypeDB is a polymorphic database with a conceptual data model, a strong subtyping... » more | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment... » more | TypeDB provides a new level of expressivity, extensibility, interoperability, and... » more | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Metadata enrichment and management, linked data publishing, semantic inferencing... » more | Life sciences : TypeDB makes working with biological data much easier and accelerates... » more | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | GraphDB provides a platform for building next-generation AI and Knowledge Graph... » 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition... » more | Apache f or language drivers, and AGPL and Commercial for the database server. The... » more | Cost-based models and subscription-based models are both available. One license is... » 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 | Microsoft Azure SQL Database formerly SQL Azure | Tarantool | TypeDB formerly named Grakn | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | PostgreSQL is the DBMS of the Year 2020 Cloud-based DBMS's popularity grows at high rates The popularity of cloud-based DBMSs has increased tenfold in four years | Data processing speed and reliability: in-memory synchronous replication | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | Ontotext's GraphDB Solution is Now Available on the Microsoft Azure Marketplace Ontotext Unveils GraphDB 10.4 with Enhanced AWS Integration and ChatGPT Connector Ontotext Platform 3.0 for Enterprise Knowledge Graphs Released Ontotext's GraphDB 8.10 Makes Knowledge Graph Experience Faster and Richer Ontotext's GraphDB 10 Brings Modern Data Architectures to the Mainstream with Better Resilience and Еаsier Operations provided by Google News | Copilot in Azure SQL Database in Private Preview Microsoft unveils Copilot for Azure SQL Database Azure SQL Database migration to OCI - resources estimation and migration approach Public Preview: New Azure SQL Database skills introduced to Microsoft Copilot in Azure | Azure updates Azure SQL Database takes Saturday off on US east coast following network power failure provided by Google News | Deploying Tarantool Cartridge applications with zero effort (Part 1) VShard — horizontal scaling in Tarantool Accelerating PHP connectors for Tarantool using Async, Swoole, and Parallel provided by Google News | An Enterprise Data Stack Using TypeDB | by Daniel Crowe Spacecraft Engineering Models: How to Migrate UML to TypeQL Modelling Biomedical Data for a Drug Discovery Knowledge Graph 195 Data Science Libraries You Should Reconsider Using | by Dimitris Effrosynidis How Roche Discovered Novel Potential Gene Targets with TypeDB provided by Google News | MapR Hadoop Upgrade Runs HP Vertica Stonebraker Seeks to Invert the Computing Paradigm with DBOS OpenText expands enterprise portfolio with AI and Micro Focus integrations Postgres pioneer Michael Stonebraker promises to upend the database once more Querying a Vertica data source in Amazon Athena using the Athena Federated Query SDK | Amazon Web Services provided by Google News |
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