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DBMS > Amazon DocumentDB vs. Amazon Redshift vs. Hazelcast

System Properties Comparison Amazon DocumentDB vs. Amazon Redshift vs. Hazelcast

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAmazon Redshift  Xexclude from comparisonHazelcast  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceLarge scale data warehouse service for use with business intelligence toolsA widely adopted in-memory data grid
Primary database modelDocument storeRelational DBMSKey-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#124  Overall
#22  Document stores
Score15.25
Rank#38  Overall
#23  Relational DBMS
Score5.72
Rank#59  Overall
#6  Key-value stores
Websiteaws.amazon.com/­documentdbaws.amazon.com/­redshifthazelcast.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.aws.amazon.com/­redshifthazelcast.org/­imdg/­docs
DeveloperAmazon (based on PostgreSQL)Hazelcast
Initial release201920122008
Current release5.3.6, November 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJava
Server operating systemshostedhostedAll OS with a Java VM
Data schemeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyes
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.nonoyes infothe object must implement a serialization strategy
Secondary indexesyesrestrictedyes
SQL infoSupport of SQLnoyes infodoes not fully support an SQL-standardSQL-like query language
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
All languages supporting JDBC/ODBC.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresnouser defined functions infoin Pythonyes infoEvent Listeners, Executor Services
Triggersnonoyes infoEvents
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infoinformational only, not enforced by the systemno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDone or two-phase-commit; repeatable reads; read commited
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardRole-based access control

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More resources
Amazon DocumentDBAmazon RedshiftHazelcast
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