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DBMS > Alibaba Cloud Table Store vs. Amazon Neptune vs. Apache IoTDB vs. Databend vs. Tkrzw

System Properties Comparison Alibaba Cloud Table Store vs. Amazon Neptune vs. Apache IoTDB vs. Databend vs. Tkrzw

Editorial information provided by DB-Engines
NameAlibaba Cloud Table Store  Xexclude from comparisonAmazon Neptune  Xexclude from comparisonApache IoTDB  Xexclude from comparisonDatabend  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionA fully managed Wide Column Store for large quantities of semi-structured data with real-time accessFast, reliable graph database built for the cloudAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelWide column storeGraph DBMS
RDF store
Time Series DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#297  Overall
#11  Wide column stores
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.alibabacloud.com/­product/­table-storeaws.amazon.com/­neptuneiotdb.apache.orggithub.com/­datafuselabs/­databend
www.databend.com
dbmx.net/­tkrzw
Technical documentationwww.alibabacloud.com/­help/­en/­tablestoreaws.amazon.com/­neptune/­developer-resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databend.com
DeveloperAlibabaAmazonApache Software FoundationDatabend LabsMikio Hirabayashi
Initial release20162017201820212020
Current release1.1.0, April 20231.0.59, April 20230.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaRustC++
Server operating systemshostedhostedAll OS with a Java VM (>= 1.8)hosted
Linux
macOS
Linux
macOS
Data schemeschema-freeschema-freeyesyesschema-free
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.nonononono
Secondary indexesnonoyesno
SQL infoSupport of SQLnonoSQL-like query languageyesno
APIs and other access methodsHTTP APIOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
Native API
CLI Client
JDBC
RESTful HTTP API
Supported programming languagesJava
Python
C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
Go
Java
JavaScript (Node.js)
Python
Rust
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnonoyesnono
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicenonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)nonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnonenone
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing specific database classes
User concepts infoAccess controlAccess rights based on subaccounts and tokensAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesUsers with fine-grained authorization concept, user rolesno

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More resources
Alibaba Cloud Table StoreAmazon NeptuneApache IoTDBDatabendTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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