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DBMS > Apache Druid vs. HarperDB vs. IBM Db2 Event Store

System Properties Comparison Apache Druid vs. HarperDB vs. IBM Db2 Event Store

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHarperDB  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Distributed Event Store optimized for Internet of Things use cases
Primary database modelRelational DBMS
Time Series DBMS
Document storeEvent Store
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.55
Rank#248  Overall
#38  Document stores
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Websitedruid.apache.orgwww.harperdb.iowww.ibm.com/­products/­db2-event-store
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.harperdb.io/­docswww.ibm.com/­docs/­en/­db2-event-store
DeveloperApache Software Foundation and contributorsHarperDBIBM
Initial release201220172017
Current release29.0.1, April 20243.1, August 20212.0
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree community edition availablecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaNode.jsC and C++
Server operating systemsLinux
OS X
Unix
Linux
OS X
Linux infoLinux, macOS, Windows for the developer addition
Data schemeyes infoschema-less columns are supporteddynamic schemayes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyes
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
Secondary indexesyesyesno
SQL infoSupport of SQLSQL for queryingSQL-like data manipulation statementsyes infothrough the embedded Spark runtime
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Server-side scripts infoStored proceduresnoCustom Functions infosince release 3.1yes
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedA table resides as a whole on one (or more) nodes in a clusterSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infothe nodes on which a table resides can be definedActive-active shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutable
Durability infoSupport for making data persistentyesyes, using LMDBYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users and rolesfine grained access rights according to SQL-standard

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More resources
Apache DruidHarperDBIBM Db2 Event Store
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