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DBMS > Amazon DocumentDB vs. Heroic vs. Hive vs. Netezza

System Properties Comparison Amazon DocumentDB vs. Heroic vs. Hive vs. Netezza

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonHeroic  Xexclude from comparisonHive  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchdata warehouse software for querying and managing large distributed datasets, built on HadoopData warehouse and analytics appliance part of IBM PureSystems
Primary database modelDocument storeTime Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#137  Overall
#24  Document stores
Score0.57
Rank#250  Overall
#21  Time Series DBMS
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score10.18
Rank#46  Overall
#29  Relational DBMS
Websiteaws.amazon.com/­documentdbgithub.com/­spotify/­heroichive.apache.orgwww.ibm.com/­products/­netezza
Technical documentationaws.amazon.com/­documentdb/­resourcesspotify.github.io/­heroiccwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperSpotifyApache Software Foundation infoinitially developed by FacebookIBM
Initial release2019201420122000
Current release3.1.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemshostedAll OS with a Java VMLinux infoincluded in appliance
Data schemeschema-freeschema-freeyesyes
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 indexesyesyes infovia Elasticsearchyesyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
Thrift
JDBC
ODBC
OLE DB
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C++
Java
PHP
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnonoyes infouser defined functions and integration of map-reduceyes
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes infoquery execution via MapReduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
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 operationsnonoACID
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.no
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and rolesUsers with fine-grained authorization concept

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More resources
Amazon DocumentDBHeroicHiveNetezza infoAlso called PureData System for Analytics by IBM
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