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DBMS > 4D vs. Apache Druid vs. IBM Db2 Event Store vs. Spark SQL

System Properties Comparison 4D vs. Apache Druid vs. IBM Db2 Event Store vs. Spark SQL

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonApache Druid  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemOpen-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 casesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMS
Time Series DBMS
Event Store
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#108  Overall
#54  Relational DBMS
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.4d.comdruid.apache.orgwww.ibm.com/­products/­db2-event-storespark.apache.org/­sql
Technical documentationdeveloper.4d.comdruid.apache.org/­docs/­latest/­designwww.ibm.com/­docs/­en/­db2-event-storespark.apache.org/­docs/­latest/­sql-programming-guide.html
Developer4D, IncApache Software Foundation and contributorsIBMApache Software Foundation
Initial release1984201220172014
Current releasev20, April 202329.0.1, April 20242.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2commercial 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 languageJavaC and C++Scala
Server operating systemsOS X
Windows
Linux
OS X
Unix
Linux infoLinux, macOS, Windows for the developer additionLinux
OS X
Windows
Data schemeyesyes infoschema-less columns are supportedyesyes
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.yesnonono
Secondary indexesyesyesnono
SQL infoSupport of SQLyes infoclose to SQL 92SQL for queryingyes infothrough the embedded Spark runtimeSQL-like DML and DDL statements
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
JDBC
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languages4D proprietary IDE
PHP
Clojure
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
Python
R
Scala
Server-side scripts infoStored proceduresyesnoyesno
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infomanual/auto, time-basedShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes, via HDFS, S3 or other storage enginesActive-active shard replicationnone
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 integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesYes - 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.nonoyesno
User concepts infoAccess controlUsers and groupsRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardno

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More resources
4D infoformer name: 4th DimensionApache DruidIBM Db2 Event StoreSpark SQL
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