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DBMS > FatDB vs. Stardog vs. Vertica

System Properties Comparison FatDB vs. Stardog vs. Vertica

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonStardog  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationCloud 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 modelDocument store
Key-value store
Graph DBMS
RDF store
Relational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.05
Rank#129  Overall
#11  Graph DBMS
#6  RDF stores
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websitewww.stardog.comwww.vertica.com
Technical documentationdocs.stardog.comvertica.com/­documentation
DeveloperFatCloudStardog-UnionOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201220102005
Current release7.3.0, May 202012.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentscommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono 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 languageC#JavaC++
Server operating systemsWindowsLinux
macOS
Windows
Linux
Data schemeschema-freeschema-free and OWL/RDFS-schema supportYes, 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 dateyesyesyes
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.no infoImport/export of XML data possibleno
Secondary indexesyesyes infosupports real-time indexing in full-text and geospatialNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLno infoVia inetgration in SQL ServerYes, compatible with all major SQL variants through dedicated BI/SQL ServerFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
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 infocharacter-based, interactive, front-end utility
Supported programming languagesC#.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infovia applicationsuser defined functions and aggregates, HTTP Server extensions in Javayes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infovia applicationsyes infovia event handlersyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-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 methodsyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency in HA-ClusterImmediate Consistency
Foreign keys infoReferential integritynoyes inforelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users and rolesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
FatDBStardogVertica 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
FatDBStardogVertica infoOpenText™ Vertica™
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