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DBMS > Alibaba Cloud Table Store vs. Apache IoTDB vs. Kinetica vs. Sadas Engine vs. Sphinx

System Properties Comparison Alibaba Cloud Table Store vs. Apache IoTDB vs. Kinetica vs. Sadas Engine vs. Sphinx

Editorial information provided by DB-Engines
NameAlibaba Cloud Table Store  Xexclude from comparisonApache IoTDB  Xexclude from comparisonKinetica  Xexclude from comparisonSadas Engine  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA fully managed Wide Column Store for large quantities of semi-structured data with real-time accessAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkFully vectorized database across both GPUs and CPUsSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelWide column storeTime Series DBMSRelational DBMSRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#297  Overall
#11  Wide column stores
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.alibabacloud.com/­product/­table-storeiotdb.apache.orgwww.kinetica.comwww.sadasengine.comsphinxsearch.com
Technical documentationwww.alibabacloud.com/­help/­en/­tablestoreiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.kinetica.comwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationsphinxsearch.com/­docs
DeveloperAlibabaApache Software FoundationKineticaSADAS s.r.l.Sphinx Technologies Inc.
Initial release20162018201220062001
Current release1.1.0, April 20237.1, August 20218.03.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercial infofree trial version availableOpen Source infoGPL version 2, commercial licence 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 languageJavaC, C++C++C++
Server operating systemshostedAll OS with a Java VM (>= 1.8)LinuxAIX
Linux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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 indexesnoyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statementsyesSQL-like query language (SphinxQL)
APIs and other access methodsHTTP APIJDBC
Native API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
Proprietary protocol
Supported programming languagesJava
Python
C
C#
C++
Go
Java
Python
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyesuser defined functionsnono
Triggersnoyesyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAMyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlAccess rights based on subaccounts and tokensyesAccess rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standardno

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Alibaba Cloud Table StoreApache IoTDBKineticaSadas EngineSphinx
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