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DBMS > EsgynDB vs. RDF4J vs. Vertica

System Properties Comparison EsgynDB vs. RDF4J vs. Vertica

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Columnar relational DBMS designed to handle modern analytic workloads, enabling fast query performance
Primary database modelRelational DBMSRDF storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.28
Rank#266  Overall
#121  Relational DBMS
Score0.55
Rank#224  Overall
#9  RDF stores
Score22.21
Rank#32  Overall
#19  Relational DBMS
Websiteesgyn.comrdf4j.orgwww.vertica.com
Technical documentationesgyn.com/­developersrdf4j.org/­documentationwww.vertica.com/­docs/­10.0.x/­HTML/­Content/­Home.htm
DeveloperEsgynSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Vertica / Micro Focus infoprior to that Hewlett Packard
Initial release201520042005
Current releaseVertica 10.0 Software, May 2020
Vertica for SQL on Hadoop 10.0 Software, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoAvailable on all major clouds - Amazon AWS, Microsoft Azure and Google Cloud Platform
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJava
Server operating systemsLinuxLinux
OS X
Unix
Windows
Linux
Data schemeyesyes infoRDF Schemasyes infoUnstructured data can be stored in specific Flex-Tables
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.noyes
Secondary indexesyesyesno infoThe concept of 'projections' can be used instead of indexes.
SQL infoSupport of SQLyesnoyes infonearly full SQL99 without support for indexes and triggers
APIs and other access methodsADO.NET
JDBC
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
ADO.NET
JDBC
Kafka
ODBC
Proprietary protocol
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetJava
PHP
Python
C++
Java
Perl
Python
R
Server-side scripts infoStored proceduresJava Stored Proceduresyesyes
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoSegmentation, Projection Segmentation, Hash Segmentation
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersnoneMulti-source replication infoCluster level and Object level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infowith Vertica Connector for Hadoop
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
EsgynDBRDF4J infoformerly known as SesameVertica infoVertica Analytics Platform
Specific characteristicsColumnar storage, MPP, Hybrid storage model, Aggressive data compression, High availability,...
» more
Competitive advantagesPerformance at exabyte scale, Deploy anywhere, Open source innovation, Analysis in...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are available
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More resources
EsgynDBRDF4J infoformerly known as SesameVertica infoVertica Analytics Platform
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