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DBMS > FatDB vs. SiteWhere vs. TigerGraph vs. Vertica

System Properties Comparison FatDB vs. SiteWhere vs. TigerGraph vs. Vertica

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonSiteWhere  Xexclude from comparisonTigerGraph  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.M2M integration platform for persisting/querying time series dataA 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 modelDocument store
Key-value store
Time Series DBMSGraph DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.05
Rank#381  Overall
#41  Time Series DBMS
Score1.92
Rank#143  Overall
#13  Graph DBMS
Score11.76
Rank#44  Overall
#28  Relational DBMS
Websitegithub.com/­sitewhere/­sitewherewww.tigergraph.comwww.vertica.com
Technical documentationsitewhere1.sitewhere.io/­index.htmldocs.tigergraph.comvertica.com/­documentation
DeveloperFatCloudSiteWhereOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2012201020172005
Current release12.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoCommon Public Attribution License Version 1.0commercialcommercial 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#JavaC++C++
Server operating systemsWindowsLinux
OS X
Windows
LinuxLinux
Data schemeschema-freepredefined schemeyesYes, 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.nonono
Secondary indexesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoSQL-like query language (GSQL)Full 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
HTTP RESTGSQL (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++
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infovia applicationsyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infovia applicationsnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on HBasehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor infobased on HBaseMulti-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 systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsUsers with fine-grained authorization conceptRole-based access controlfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
FatDBSiteWhereTigerGraphVertica 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,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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FatDBSiteWhereTigerGraphVertica infoOpenText™ Vertica™
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