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DBMS > RDF4J vs. SingleStore vs. VelocityDB vs. Vertica vs. Yaacomo

System Properties Comparison RDF4J vs. SingleStore vs. VelocityDB vs. Vertica vs. Yaacomo

Editorial information provided by DB-Engines
NameRDF4J infoformerly known as Sesame  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonVelocityDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table typeA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)Cloud 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.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRDF storeRelational DBMSGraph DBMS
Object oriented DBMS
Relational DBMS infoColumn orientedRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.69
Rank#230  Overall
#9  RDF stores
Score5.60
Rank#62  Overall
#35  Relational DBMS
Score0.05
Rank#358  Overall
#36  Graph DBMS
#16  Object oriented DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiterdf4j.orgwww.singlestore.comvelocitydb.comwww.vertica.comyaacomo.com
Technical documentationrdf4j.org/­documentationdocs.singlestore.comvelocitydb.com/­UserGuidevertica.com/­documentation
DeveloperSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.SingleStore Inc.VelocityDB IncOpenText infopreviously Micro Focus and Hewlett PackardQ2WEB GmbH
Initial release20042013201120052009
Current release8.5, January 20247.x12.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoEclipse Distribution License (EDL), v1.0.commercial infofree developer edition availablecommercialcommercial infoLimited community edition freecommercial
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

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SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageJavaC++, GoC#C++
Server operating systemsLinux
OS X
Unix
Windows
Linux info64 bit version requiredAny that supports .NETLinuxAndroid
Linux
Windows
Data schemeyes infoRDF SchemasyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.yes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nononono
Secondary indexesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLnoyes infobut no triggers and foreign keysnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.yes
APIs and other access methodsJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
.NetADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
JDBC
ODBC
Supported programming languagesJava
PHP
Python
Bash
C
C#
Java
JavaScript (Node.js)
Python
.NetC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesyesnoyes, PostgreSQL PL/pgSQL, with minor differences
TriggersyesnoCallbacks are triggered when data changesyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infohash partitioningShardinghorizontal partitioning, hierarchical partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication infostores two copies of each physical data partition on two separate nodesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infocan define user-defined aggregate functions for map-reduce-style calculationsnono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoIsolation support depends on the API usedACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyes infoin-memory storage is supported as wellyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlnoFine grained access control via users, groups and rolesBased on Windows Authenticationfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashfine grained access rights according to SQL-standard
More information provided by the system vendor
RDF4J infoformerly known as SesameSingleStore infoformer name was MemSQLVelocityDBVertica infoOpenText™ Vertica™Yaacomo
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Market metricsCustomers in various industries worldwide including US and International Industry...
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Licensing and pricing modelsF ree Tier and Enterprise Edition
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Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
RDF4J infoformerly known as SesameSingleStore infoformer name was MemSQLVelocityDBVertica infoOpenText™ Vertica™Yaacomo
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