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DBMS > Apache Druid vs. IBM Db2 Event Store vs. RDF4J vs. Rockset

System Properties Comparison Apache Druid vs. IBM Db2 Event Store vs. RDF4J vs. Rockset

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonRockset  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDistributed 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 RocksDB
Primary database modelRelational DBMS
Time Series DBMS
Event Store
Time Series DBMS
RDF storeDocument store
Secondary database modelsRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.29
Rank#95  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score0.23
Rank#316  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.71
Rank#231  Overall
#9  RDF stores
Score0.84
Rank#209  Overall
#35  Document stores
Websitedruid.apache.orgwww.ibm.com/­products/­db2-event-storerdf4j.orgrockset.com
Technical documentationdruid.apache.org/­docs/­latest/­designwww.ibm.com/­docs/­en/­db2-event-storerdf4j.org/­documentationdocs.rockset.com
DeveloperApache Software Foundation and contributorsIBMSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Rockset
Initial release2012201720042019
Current release29.0.1, April 20242.0
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree developer edition availableOpen Source infoEclipse Distribution License (EDL), v1.0.commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++JavaC++
Server operating systemsLinux
OS X
Unix
Linux infoLinux, macOS, Windows for the developer additionLinux
OS X
Unix
Windows
hosted
Data schemeyes infoschema-less columns are supportedyesyes infoRDF Schemasschema-free
Typing infopredefined data types such as float or dateyesyesyesdynamic typing
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.nonono infoingestion from XML files supported
Secondary indexesyesnoyesall fields are automatically indexed
SQL infoSupport of SQLSQL for queryingyes infothrough the embedded Spark runtimenoRead-only SQL queries, including JOINs
APIs and other access methodsJDBC
RESTful HTTP/JSON API
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
HTTP REST
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
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
Server-side scripts infoStored proceduresnoyesyesno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingnoneAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesActive-active shard replicationnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoIsolation support depends on the API usedno
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.noyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardnoAccess rights for users and organizations can be defined via Rockset console

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More resources
Apache DruidIBM Db2 Event StoreRDF4J infoformerly known as SesameRockset
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