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DBMS > Firebolt vs. RDF4J vs. SiteWhere vs. Vertica

System Properties Comparison Firebolt vs. RDF4J vs. SiteWhere vs. Vertica

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Editorial information provided by DB-Engines
NameFirebolt  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSiteWhere  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionHighly scalable cloud data warehouse and analytics product infoForked from ClickhouseRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.M2M integration platform for persisting/querying time series dataCloud 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 modelRelational DBMSRDF storeTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.73
Rank#140  Overall
#63  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitewww.firebolt.iordf4j.orggithub.com/­sitewhere/­sitewherewww.vertica.com
Technical documentationdocs.firebolt.iordf4j.org/­documentationsitewhere1.sitewhere.io/­index.htmlvertica.com/­documentation
DeveloperFirebolt Analytics Inc.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.SiteWhereOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2020200420102005
Current release12.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoCommon Public Attribution License Version 1.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnonono 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 languageJavaJavaC++
Server operating systemshostedLinux
OS X
Unix
Windows
Linux
OS X
Windows
Linux
Data schemeyesyes infoRDF Schemaspredefined schemeYes, 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 indexesyesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesnonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methods.Net
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
HTTP RESTADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGo
JavaScript (Node.js)
Python
Java
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infobased on HBasehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layernoneselectable 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 methodsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoIsolation support depends on the API usednoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
FireboltRDF4J infoformerly known as SesameSiteWhereVertica 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
FireboltRDF4J infoformerly known as SesameSiteWhereVertica infoOpenText™ Vertica™
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