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DBMS > Amazon Neptune vs. Apache IoTDB vs. Cloudflare Workers KV vs. Databend vs. Tkrzw

System Properties Comparison Amazon Neptune vs. Apache IoTDB vs. Cloudflare Workers KV vs. Databend vs. Tkrzw

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache IoTDB  Xexclude from comparisonCloudflare Workers KV  Xexclude from comparisonDatabend  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionFast, 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 FlinkA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.An 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 modelGraph DBMS
RDF store
Time Series DBMSKey-value storeRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.39
Rank#274  Overall
#39  Key-value stores
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websiteaws.amazon.com/­neptuneiotdb.apache.orgwww.cloudflare.com/­developer-platform/­workers-kvgithub.com/­datafuselabs/­databend
www.databend.com
dbmx.net/­tkrzw
Technical documentationaws.amazon.com/­neptune/­developer-resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldevelopers.cloudflare.com/­kv/­apidocs.databend.com
DeveloperAmazonApache Software FoundationCloudflareDatabend LabsMikio Hirabayashi
Initial release20172018201820212020
Current release1.1.0, April 20231.0.59, April 20230.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaRustC++
Server operating systemshostedAll OS with a Java VM (>= 1.8)hostedhosted
Linux
macOS
Linux
macOS
Data schemeschema-freeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesnoyesno
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 indexesnoyesnono
SQL infoSupport of SQLnoSQL-like query languagenoyesno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
Native API
HTTP REST
Proprietary protocol
CLI Client
JDBC
RESTful HTTP API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
Go
Java
JavaScript (Node.js)
Python
Rust
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnoyesnonono
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)nonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-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 replicasyesnonenone
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
Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infousing specific database classes
User concepts infoAccess controlAccess 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
Amazon NeptuneApache IoTDBCloudflare Workers KVDatabendTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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