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DBMS > Amazon DocumentDB vs. Apache Phoenix vs. Riak TS vs. Spark SQL

System Properties Comparison Amazon DocumentDB vs. Apache Phoenix vs. Riak TS vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonRiak TS  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA scale-out RDBMS with evolutionary schema built on Apache HBaseRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KVSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#137  Overall
#24  Document stores
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score0.25
Rank#308  Overall
#26  Time Series DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­documentdbphoenix.apache.orgspark.apache.org/­sql
Technical documentationaws.amazon.com/­documentdb/­resourcesphoenix.apache.orgwww.tiot.jp/­riak-docs/­riak/­ts/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationOpen Source, formerly Basho TechnologiesApache Software Foundation
Initial release2019201420152014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.0.0, September 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open SourceOpen 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 languageJavaErlangScala
Server operating systemshostedLinux
Unix
Windows
Linux
OS X
Linux
OS X
Windows
Data schemeschema-freeyes infolate-bound, schema-on-read capabilitiesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyesyesrestrictedno
SQL infoSupport of SQLnoyesyes, limitedSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBCHTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsErlangno
Triggersnonoyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes, 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 replicasMulti-source replication
Source-replica replication
selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Hadoop integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenono infolinks between datasets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDnono
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.yesno
User concepts infoAccess controlAccess rights for users and rolesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynono

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More resources
Amazon DocumentDBApache PhoenixRiak TSSpark SQL
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