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DBMS > IBM Db2 Event Store vs. RDF4J vs. Rockset vs. YDB

System Properties Comparison IBM Db2 Event Store vs. RDF4J vs. Rockset vs. YDB

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Editorial information provided by DB-Engines
NameIBM Db2 Event Store  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonRockset  Xexclude from comparisonYDB  Xexclude from comparison
DescriptionDistributed 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.A scalable, reliable search and analytics service in the cloud, built on RocksDBA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelEvent Store
Time Series DBMS
RDF storeDocument storeDocument store
Relational DBMS
Secondary database modelsRelational DBMS
Search engine
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
Score0.82
Rank#212  Overall
#36  Document stores
Score0.33
Rank#287  Overall
#43  Document stores
#132  Relational DBMS
Websitewww.ibm.com/­products/­db2-event-storerdf4j.orgrockset.comgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationwww.ibm.com/­docs/­en/­db2-event-storerdf4j.org/­documentationdocs.rockset.comydb.tech/­en/­docs
DeveloperIBMSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.RocksetYandex
Initial release2017200420192019
Current release2.0
License infoCommercial or Open Sourcecommercial infofree developer edition availableOpen Source infoEclipse Distribution License (EDL), v1.0.commercialOpen Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++JavaC++
Server operating systemsLinux infoLinux, macOS, Windows for the developer additionLinux
OS X
Unix
Windows
hostedLinux
Data schemeyesyes infoRDF Schemasschema-freeFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyesdynamic typingyes
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 infoingestion from XML files supportedno
Secondary indexesnoyesall fields are automatically indexedyes
SQL infoSupport of SQLyes infothrough the embedded Spark runtimenoRead-only SQL queries, including JOINsSQL-like query language (YQL)
APIs and other access methodsADO.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
HTTP RESTRESTful HTTP API (DynamoDB compatible)
Supported programming languagesC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Java
PHP
Python
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresyesyesnono
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesActive-active shard replicationnoneyesActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoIsolation support depends on the API usednoACID
Concurrency infoSupport for concurrent manipulation of dataNo - written data is immutableyesyesyes
Durability infoSupport for making data persistentYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes 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.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users and organizations can be defined via Rockset consoleAccess rights defined for Yandex Cloud users

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More resources
IBM Db2 Event StoreRDF4J infoformerly known as SesameRocksetYDB
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