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DBMS > Apache IoTDB vs. Cloudflare Workers KV vs. Trafodion vs. Vitess

System Properties Comparison Apache IoTDB vs. Cloudflare Workers KV vs. Trafodion vs. Vitess

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCloudflare Workers KV  Xexclude from comparisonTrafodion  Xexclude from comparisonVitess  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn 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.Transactional SQL-on-Hadoop DBMSScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelTime Series DBMSKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.39
Rank#274  Overall
#39  Key-value stores
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websiteiotdb.apache.orgwww.cloudflare.com/­developer-platform/­workers-kvtrafodion.apache.orgvitess.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldevelopers.cloudflare.com/­kv/­apitrafodion.apache.org/­documentation.htmlvitess.io/­docs
DeveloperApache Software FoundationCloudflareApache Software Foundation, originally developed by HPThe Linux Foundation, PlanetScale
Initial release2018201820142013
Current release1.1.0, April 20232.3.0, February 201915.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaGo
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinuxDocker
Linux
macOS
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.nonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query languagenoyesyes infowith proprietary extensions
APIs and other access methodsJDBC
Native API
HTTP REST
Proprietary protocol
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
All languages supporting JDBC/ODBC/ADO.NetAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnoJava Stored Proceduresyes infoproprietary syntax
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesyes, via HBaseMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes infovia user defined functions and HBaseno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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More resources
Apache IoTDBCloudflare Workers KVTrafodionVitess
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