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DBMS > Apache IoTDB vs. CockroachDB vs. FatDB vs. Vitess

System Properties Comparison Apache IoTDB vs. CockroachDB vs. FatDB vs. Vitess

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCockroachDB  Xexclude from comparisonFatDB  Xexclude from comparisonVitess  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the 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 FlinkCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Scalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelTime Series DBMSRelational DBMSDocument store
Key-value store
Relational 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
Score5.73
Rank#58  Overall
#34  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websiteiotdb.apache.orgwww.cockroachlabs.comvitess.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.cockroachlabs.com/­docsvitess.io/­docs
DeveloperApache Software FoundationCockroach LabsFatCloudThe Linux Foundation, PlanetScale
Initial release2018201520122013
Current release1.1.0, April 202324.1.0, May 202415.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0, commercial license availablecommercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoC#Go
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
macOS
Windows
WindowsDocker
Linux
macOS
Data schemeyesdynamic schemaschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageyes, wire compatible with PostgreSQLno infoVia inetgration in SQL Serveryes infowith proprietary extensions
APIs and other access methodsJDBC
Native API
JDBC.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
C#Ada
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 proceduresyesnoyes infovia applicationsyes infoproprietary syntax
Triggersyesnoyes infovia applicationsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication using RAFTselectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID 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.yesnoyes
User concepts infoAccess controlyesRole-based access controlno infoCan implement custom security layer via applicationsUsers with fine-grained authorization concept infono user groups or roles

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More resources
Apache IoTDBCockroachDBFatDBVitess
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