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DBMS > Apache IoTDB vs. HBase vs. Sqrrl vs. Vitess

System Properties Comparison Apache IoTDB vs. HBase vs. Sqrrl vs. Vitess

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHBase  Xexclude from comparisonSqrrl  Xexclude from comparisonVitess  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed 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 FlinkWide-column store based on Apache Hadoop and on concepts of BigTableAdaptable, secure NoSQL built on Apache AccumuloScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelTime Series DBMSWide column storeDocument store
Graph DBMS
Key-value store
Wide column 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
Score27.97
Rank#26  Overall
#2  Wide column stores
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websiteiotdb.apache.orghbase.apache.orgsqrrl.comvitess.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhbase.apache.org/­book.htmlvitess.io/­docs
DeveloperApache Software FoundationApache Software Foundation infoApache top-level project, originally developed by PowersetAmazon infooriginally Sqrrl Data, Inc.The Linux Foundation, PlanetScale
Initial release2018200820122013
Current release1.1.0, April 20232.3.4, January 202115.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache version 2commercialOpen 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 languageJavaJavaJavaGo
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Unix
Windows infousing Cygwin
LinuxDocker
Linux
macOS
Data schemeyesschema-free, schema definition possibleschema-freeyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes
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 indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query languagenonoyes infowith proprietary extensions
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP API
Thrift
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
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 proceduresyesyes infoCoprocessors in Javanoyes infoproprietary syntax
Triggersyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infomaking use of HadoopSharding
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
Source-replica replication
selectable replication factor infomaking use of HadoopMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynononoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)Atomic updates per row, document, or graph entityACID 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.yesyesyes
User concepts infoAccess controlyesAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)Users with fine-grained authorization concept infono user groups or roles

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More resources
Apache IoTDBHBaseSqrrlVitess
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