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DBMS > Amazon DocumentDB vs. Apache Drill vs. Apache Phoenix vs. Datomic vs. Spark SQL

System Properties Comparison Amazon DocumentDB vs. Apache Drill vs. Apache Phoenix vs. Datomic vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Drill  Xexclude from comparisonApache Phoenix  Xexclude from comparisonDatomic  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageA scale-out RDBMS with evolutionary schema built on Apache HBaseDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilitySpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeDocument store
Relational DBMS
Relational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score1.95
Rank#127  Overall
#23  Document stores
#60  Relational DBMS
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­documentdbdrill.apache.orgphoenix.apache.orgwww.datomic.comspark.apache.org/­sql
Technical documentationaws.amazon.com/­documentdb/­resourcesdrill.apache.org/­docsphoenix.apache.orgdocs.datomic.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationApache Software FoundationCognitectApache Software Foundation
Initial release20192012201420122014
Current release1.20.3, January 20235.0-HBase2, July 2018 and 4.15-HBase1, December 20191.0.6735, June 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0commercial infolimited edition freeOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ClojureScala
Server operating systemshostedLinux
OS X
Windows
Linux
Unix
Windows
All OS with a Java VMLinux
OS X
Windows
Data schemeschema-freeschema-freeyes infolate-bound, schema-on-read capabilitiesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonononono
Secondary indexesyesnoyesyesno
SQL infoSupport of SQLnoSQL SELECT statement is SQL:2003 compliantyesnoSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
RESTful HTTP API
JDBCRESTful HTTP APIJDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C++C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Clojure
Java
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsuser defined functionsyes infoTransaction Functionsno
TriggersnononoBy using transaction functionsno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnone infoBut extensive use of caching in the application peersyes, 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
none infoBut extensive use of caching in the application peersnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesDepending on the underlying data sourceyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourceyesyes inforecommended only for testing and developmentno
User concepts infoAccess controlAccess rights for users and rolesDepending on the underlying data sourceAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynono

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More resources
Amazon DocumentDBApache DrillApache PhoenixDatomicSpark SQL
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