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DBMS > Adabas vs. Apache Druid vs. Apache IoTDB vs. Drizzle vs. SWC-DB

System Properties Comparison Adabas vs. Apache Druid vs. Apache IoTDB vs. Drizzle vs. SWC-DB

Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonApache Druid  Xexclude from comparisonApache IoTDB  Xexclude from comparisonDrizzle  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A high performance, scalable Wide Column DBMS
Primary database modelMultivalue DBMSRelational DBMS
Time Series DBMS
Time Series DBMSRelational DBMSWide column store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.17
Rank#94  Overall
#1  Multivalue DBMS
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmldruid.apache.orgiotdb.apache.orggithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdruid.apache.org/­docs/­latest/­designiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.html
DeveloperSoftware AGApache Software Foundation and contributorsApache Software FoundationDrizzle project, originally started by Brian AkerAlex Kashirin
Initial release19712012201820082020
Current release29.0.1, April 20241.1.0, April 20237.2.4, September 20120.5, April 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2Open Source infoApache Version 2.0Open Source infoGNU GPLOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++C++
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
Linux
OS X
Unix
All OS with a Java VM (>= 1.8)FreeBSD
Linux
OS X
Linux
Data schemeyesyes infoschema-less columns are supportedyesyesschema-free
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 indexesyesyesyesyes
SQL infoSupport of SQLyes infowith add-on product Adabas SQL GatewaySQL for queryingSQL-like query languageyes infowith proprietary extensionsSQL-like query language
APIs and other access methodsHTTP API infowith add-on software Adabas SOA Gateway
SOAP-based API infowith add-on software Adabas SOA Gateway
JDBC
RESTful HTTP/JSON API
JDBC
Native API
JDBCProprietary protocol
Thrift
Supported programming languagesNaturalClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
C
C++
Java
PHP
C++
Server-side scripts infoStored proceduresin Naturalnoyesnono
Triggersnonoyesno infohooks for callbacks inside the server can be used.no
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistaSharding infomanual/auto, time-basedhorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event Replicatoryes, via HDFS, S3 or other storage enginesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlonly with OS-specific tools (e.g. IBM RACF, CA Top Secret)RBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesPluggable authentication mechanisms infoe.g. LDAP, HTTP

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More resources
Adabas infodenotes "adaptable data base"Apache DruidApache IoTDBDrizzleSWC-DB infoSuper Wide Column Database
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