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DBMS > Apache Druid vs. Apache IoTDB vs. Microsoft Azure Table Storage vs. Warp 10

System Properties Comparison Apache Druid vs. Apache IoTDB vs. Microsoft Azure Table Storage vs. Warp 10

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache IoTDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionOpen-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 FlinkA Wide Column Store for rapid development using massive semi-structured datasetsTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMSWide column storeTime 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
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitedruid.apache.orgiotdb.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tableswww.warp10.io
Technical documentationdruid.apache.org/­docs/­latest/­designiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.warp10.io/­content/­02_Getting_started
DeveloperApache Software Foundation and contributorsApache Software FoundationMicrosoftSenX
Initial release2012201820122015
Current release29.0.1, April 20241.1.0, April 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0commercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemsLinux
OS X
Unix
All OS with a Java VM (>= 1.8)hostedLinux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesschema-freeschema-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 indexesyesyesnono
SQL infoSupport of SQLSQL for queryingSQL-like query languagenono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
Native API
RESTful HTTP APIHTTP API
Jupyter
WebSocket
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyesnoyes infoWarpScript
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoImplicit feature of the cloud serviceSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesAccess rights based on private key authentication or shared access signaturesMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Apache DruidApache IoTDBMicrosoft Azure Table StorageWarp 10
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