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DBMS > Graph Engine vs. RavenDB vs. Stardog vs. TigerGraph vs. Vertica

System Properties Comparison Graph Engine vs. RavenDB vs. Stardog vs. TigerGraph vs. Vertica

Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonRavenDB  Xexclude from comparisonStardog  Xexclude from comparisonTigerGraph  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationA 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 modelGraph DBMS
Key-value store
Document storeGraph DBMS
RDF store
Graph DBMSRelational DBMS infoColumn oriented
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score2.92
Rank#101  Overall
#18  Document stores
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Score1.83
Rank#139  Overall
#13  Graph DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.graphengine.ioravendb.netwww.stardog.comwww.tigergraph.comwww.vertica.com
Technical documentationwww.graphengine.io/­docs/­manualravendb.net/­docsdocs.stardog.comdocs.tigergraph.comvertica.com/­documentation
DeveloperMicrosoftHibernating RhinosStardog-UnionOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20102010201020172005
Current release5.4, July 20227.3.0, May 202012.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoAGPL version 3, commercial license availablecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentscommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation language.NET and CC#JavaC++C++
Server operating systems.NETLinux
macOS
Raspberry Pi
Windows
Linux
macOS
Windows
LinuxLinux
Data schemeyesschema-freeschema-free and OWL/RDFS-schema supportyesYes, 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 dateyesnoyesyesyes
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 infoImport/export of XML data possiblenono
Secondary indexesyesyes infosupports real-time indexing in full-text and geospatialNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like query language (RQL)Yes, compatible with all major SQL variants through dedicated BI/SQL ServerSQL-like query language (GSQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP API.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
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 languagesC#
C++
F#
Visual Basic
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
C++
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesyesuser defined functions and aggregates, HTTP Server extensions in Javayesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesyes infovia event handlersnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-source replication in HA-ClusterMulti-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 methodsyesnoyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency in HA-ClusterImmediate Consistency
Foreign keys infoReferential integritynonoyes inforelationships in graphsyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID, Cluster-wide transaction availableACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlAuthorization levels configured per client per databaseAccess rights for users and rolesRole-based access controlfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Graph Engine infoformer name: TrinityRavenDBStardogTigerGraphVertica 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
Graph Engine infoformer name: TrinityRavenDBStardogTigerGraphVertica infoOpenText™ Vertica™
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