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DBMS > Amazon DocumentDB vs. Apache IoTDB vs. Apache Phoenix vs. Spark SQL

System Properties Comparison Amazon DocumentDB vs. Apache IoTDB vs. Apache Phoenix vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAn 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 scale-out RDBMS with evolutionary schema built on Apache HBaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeTime Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­documentdbiotdb.apache.orgphoenix.apache.orgspark.apache.org/­sql
Technical documentationaws.amazon.com/­documentdb/­resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlphoenix.apache.orgspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationApache Software FoundationApache Software Foundation
Initial release2019201820142014
Current release1.1.0, April 20235.0-HBase2, July 2018 and 4.15-HBase1, December 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScala
Server operating systemshostedAll OS with a Java VM (>= 1.8)Linux
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyes infolate-bound, schema-on-read capabilitiesyes
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoSQL-like query languageyesSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
Native API
JDBCJDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Java
Python
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesuser defined functionsno
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Integration with Hadoop and SparkHadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesyesno
User concepts infoAccess controlAccess rights for users and rolesyesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyno

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More resources
Amazon DocumentDBApache IoTDBApache PhoenixSpark SQL
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