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DBMS > RDF4J vs. SurrealDB vs. TigerGraph vs. Vertica

System Properties Comparison RDF4J vs. SurrealDB vs. TigerGraph vs. Vertica

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Editorial information provided by DB-Engines
NameRDF4J infoformerly known as Sesame  Xexclude from comparisonSurrealDB  Xexclude from comparisonTigerGraph  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.A fully ACID transactional, developer-friendly, multi-model DBMSA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeCloud 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 modelRDF storeDocument store
Graph DBMS
Graph DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#222  Overall
#9  RDF stores
Score1.02
Rank#190  Overall
#33  Document stores
#18  Graph DBMS
Score1.80
Rank#138  Overall
#13  Graph DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websiterdf4j.orgsurrealdb.comwww.tigergraph.comwww.vertica.com
Technical documentationrdf4j.org/­documentationsurrealdb.com/­docsdocs.tigergraph.comvertica.com/­documentation
DeveloperSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.SurrealDB LtdOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2004202220172005
Current releasev1.5.0, May 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoEclipse Distribution License (EDL), v1.0.Open Sourcecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaRustC++C++
Server operating systemsLinux
OS X
Unix
Windows
Linux
macOS
Windows
LinuxLinux
Data schemeyes infoRDF Schemasschema-freeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono
Secondary indexesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like query languageSQL-like query language (GSQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
GraphQL
RESTful HTTP API
WebSocket
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJava
PHP
Python
Deno
Go
JavaScript (Node.js)
Rust
C++
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoIsolation support depends on the API usedACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infoin-memory storage is supported as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoyes, based on authentication and database rulesRole-based access controlfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
RDF4J infoformerly known as SesameSurrealDBTigerGraphVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
RDF4J infoformerly known as SesameSurrealDBTigerGraphVertica infoOpenText™ Vertica™
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