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DBMS > Alibaba Cloud Table Store vs. Apache Druid vs. Apache IoTDB vs. Postgres-XL vs. Splice Machine

System Properties Comparison Alibaba Cloud Table Store vs. Apache Druid vs. Apache IoTDB vs. Postgres-XL vs. Splice Machine

Editorial information provided by DB-Engines
NameAlibaba Cloud Table Store  Xexclude from comparisonApache Druid  Xexclude from comparisonApache IoTDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA fully managed Wide Column Store for large quantities of semi-structured data with real-time accessOpen-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 FlinkBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelWide column storeRelational DBMS
Time Series DBMS
Time Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#294  Overall
#12  Wide column stores
Score2.85
Rank#96  Overall
#50  Relational DBMS
#6  Time Series DBMS
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.43
Rank#260  Overall
#119  Relational DBMS
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websitewww.alibabacloud.com/­product/­table-storedruid.apache.orgiotdb.apache.orgwww.postgres-xl.orgsplicemachine.com
Technical documentationwww.alibabacloud.com/­help/­en/­tablestoredruid.apache.org/­docs/­latest/­designiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.postgres-xl.org/­documentationsplicemachine.com/­how-it-works
DeveloperAlibabaApache Software Foundation and contributorsApache Software FoundationSplice Machine
Initial release2016201220182014 infosince 2012, originally named StormDB2014
Current release30.0.0, June 20241.1.0, April 202310 R1, October 20183.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2Open Source infoApache Version 2.0Open Source infoMozilla public licenseOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaCJava
Server operating systemshostedLinux
OS X
Unix
All OS with a Java VM (>= 1.8)Linux
macOS
Linux
OS X
Solaris
Windows
Data schemeschema-freeyes infoschema-less columns are supportedyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nononoyes infoXML type, but no XML query functionality
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoSQL for queryingSQL-like query languageyes infodistributed, parallel query executionyes
APIs and other access methodsHTTP APIJDBC
RESTful HTTP/JSON API
JDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
Native Spark Datasource
ODBC
Supported programming languagesJava
Python
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesuser defined functionsyes infoJava
Triggersnonoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infomanual/auto, time-basedhorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceyes, 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 SparknoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnonoACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
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.nonoyesnoyes
User concepts infoAccess controlAccess rights based on subaccounts and tokensRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
Alibaba Cloud Table StoreApache DruidApache IoTDBPostgres-XLSplice Machine
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