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DBMS > Apache Druid vs. Ehcache vs. IBM Db2 Event Store vs. Trafodion

System Properties Comparison Apache Druid vs. Ehcache vs. IBM Db2 Event Store vs. Trafodion

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonEhcache  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA widely adopted Java cache with tiered storage optionsDistributed Event Store optimized for Internet of Things use casesTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeEvent Store
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score4.64
Rank#68  Overall
#8  Key-value stores
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Websitedruid.apache.orgwww.ehcache.orgwww.ibm.com/­products/­db2-event-storetrafodion.apache.org
Technical documentationdruid.apache.org/­docs/­latest/­designwww.ehcache.org/­documentationwww.ibm.com/­docs/­en/­db2-event-storetrafodion.apache.org/­documentation.html
DeveloperApache Software Foundation and contributorsTerracotta Inc, owned by Software AGIBMApache Software Foundation, originally developed by HP
Initial release2012200920172014
Current release29.0.1, April 20243.10.0, March 20222.02.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; commercial licenses availablecommercial infofree developer edition availableOpen 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 languageJavaJavaC and C++C++, Java
Server operating systemsLinux
OS X
Unix
All OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionLinux
Data schemeyes infoschema-less columns are supportedschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesnonoyes
SQL infoSupport of SQLSQL for queryingnoyes infothrough the embedded Spark runtimeyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JCacheADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
JavaC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnonoyesJava Stored Procedures
Triggersnoyes infoCache Event Listenersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infoby using Terracotta ServerShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoby using Terracotta ServerActive-active shard replicationyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes infosupports JTA and can work as an XA resourcenoACID
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache DruidEhcacheIBM Db2 Event StoreTrafodion
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