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DBMS > Alibaba Cloud Table Store vs. Apache IoTDB vs. Google Cloud Datastore vs. RDF4J vs. SwayDB

System Properties Comparison Alibaba Cloud Table Store vs. Apache IoTDB vs. Google Cloud Datastore vs. RDF4J vs. SwayDB

Editorial information provided by DB-Engines
NameAlibaba Cloud Table Store  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSwayDB  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 FlinkAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelWide column storeTime Series DBMSDocument storeRDF storeKey-value store
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
Score4.36
Rank#72  Overall
#12  Document stores
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.04
Rank#387  Overall
#61  Key-value stores
Websitewww.alibabacloud.com/­product/­table-storeiotdb.apache.orgcloud.google.com/­datastorerdf4j.orgswaydb.simer.au
Technical documentationwww.alibabacloud.com/­help/­en/­tablestoreiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcloud.google.com/­datastore/­docsrdf4j.org/­documentation
DeveloperAlibabaApache Software FoundationGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Simer Plaha
Initial release20162018200820042018
Current release1.1.0, April 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScala
Server operating systemshostedAll OS with a Java VM (>= 1.8)hostedLinux
OS X
Unix
Windows
Data schemeschema-freeyesschema-freeyes infoRDF Schemasschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereyesno
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 indexesnoyesyesyesno
SQL infoSupport of SQLnoSQL-like query languageSQL-like query language (GQL)nono
APIs and other access methodsHTTP APIJDBC
Native API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesJava
Python
C
C#
C++
Go
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnoyesusing Google App Engineyesno
TriggersnoyesCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingnonenone
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 replicasMulti-source replication using Paxosnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparkyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoIsolation support depends on the API usedAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights based on subaccounts and tokensyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
Alibaba Cloud Table StoreApache IoTDBGoogle Cloud DatastoreRDF4J infoformerly known as SesameSwayDB
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