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DBMS > Hypertable vs. IBM Db2 Event Store vs. RDF4J vs. Trafodion

System Properties Comparison Hypertable vs. IBM Db2 Event Store vs. RDF4J vs. Trafodion

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTrafodion  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopDistributed Event Store optimized for Internet of Things use casesRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Transactional SQL-on-Hadoop DBMS
Primary database modelWide column storeEvent Store
Time Series DBMS
RDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websitewww.ibm.com/­products/­db2-event-storerdf4j.orgtrafodion.apache.org
Technical documentationwww.ibm.com/­docs/­en/­db2-event-storerdf4j.org/­documentationtrafodion.apache.org/­documentation.html
DeveloperHypertable Inc.IBMSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Apache Software Foundation, originally developed by HP
Initial release2009201720042014
Current release0.9.8.11, March 20162.02.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availablecommercial infofree developer edition availableOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++JavaC++, Java
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
Linux infoLinux, macOS, Windows for the developer additionLinux
OS X
Unix
Windows
Linux
Data schemeschema-freeyesyes infoRDF Schemasyes
Typing infopredefined data types such as float or datenoyesyesyes
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 indexesrestricted infoonly exact value or prefix value scansnoyesyes
SQL infoSupport of SQLnoyes infothrough the embedded Spark runtimenoyes
APIs and other access methodsC++ API
Thrift
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
ADO.NET
JDBC
ODBC
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Java
PHP
Python
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnoyesyesJava Stored Procedures
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelActive-active shard replicationnoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes 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.yesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
HypertableIBM Db2 Event StoreRDF4J infoformerly known as SesameTrafodion
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