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DBMS > Amazon DocumentDB vs. Apache IoTDB vs. Hazelcast vs. Manticore Search

System Properties Comparison Amazon DocumentDB vs. Apache IoTDB vs. Hazelcast vs. Manticore Search

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonHazelcast  Xexclude from comparisonManticore Search  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 widely adopted in-memory data gridMulti-storage database for search, including full-text search.
Primary database modelDocument storeTime Series DBMSKey-value storeSearch engine
Secondary database modelsDocument store infoJSON support with IMDG 3.12Time Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.29
Rank#302  Overall
#21  Search engines
Websiteaws.amazon.com/­documentdbiotdb.apache.orghazelcast.commanticoresearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhazelcast.org/­imdg/­docsmanual.manticoresearch.com
DeveloperApache Software FoundationHazelcastManticore Software
Initial release2019201820082017
Current release1.1.0, April 20235.3.6, November 20236.0, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemshostedAll OS with a Java VM (>= 1.8)All OS with a Java VMFreeBSD
Linux
macOS
Windows
Data schemeschema-freeyesschema-freeFixed schema
Typing infopredefined data types such as float or dateyesyesyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean
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 strategyCan index from XML
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query languageSQL-like query languageSQL-like query language
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
Native API
JCache
JPA
Memcached protocol
RESTful HTTP API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Java
Python
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresnoyesyes infoEvent Listeners, Executor Servicesuser defined functions
Triggersnoyesyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
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 replicasyes infoReplicated MapSynchronous replication based on Galera library
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Integration with Hadoop and Sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
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 operationsnoone or two-phase-commit; repeatable reads; read commitedyes infoisolated transactions for atomic changes and binary logging for safe writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Manticore index.
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 rolesyesRole-based access controlno

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More resources
Amazon DocumentDBApache IoTDBHazelcastManticore Search
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