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DBMS > Amazon DocumentDB vs. Google Cloud Datastore vs. Hazelcast vs. Manticore Search

System Properties Comparison Amazon DocumentDB vs. Google Cloud Datastore vs. Hazelcast vs. Manticore Search

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHazelcast  Xexclude from comparisonManticore Search  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA widely adopted in-memory data gridMulti-storage database for search, including full-text search.
Primary database modelDocument storeDocument storeKey-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#124  Overall
#22  Document stores
Score4.13
Rank#71  Overall
#12  Document stores
Score5.72
Rank#59  Overall
#6  Key-value stores
Score0.23
Rank#301  Overall
#21  Search engines
Websiteaws.amazon.com/­documentdbcloud.google.com/­datastorehazelcast.commanticoresearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcescloud.google.com/­datastore/­docshazelcast.org/­imdg/­docsmanual.manticoresearch.com
DeveloperGoogleHazelcastManticore Software
Initial release2019200820082017
Current release5.3.6, November 20236.0, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedhostedAll OS with a Java VMFreeBSD
Linux
macOS
Windows
Data schemeschema-freeschema-freeschema-freeFixed schema
Typing infopredefined data types such as float or dateyesyes, details hereyesInt, 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 language (GQL)SQL-like query languageSQL-like query language
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC (using protocol buffers) API
RESTful HTTP/JSON 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
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresnousing Google App Engineyes infoEvent Listeners, Executor Servicesuser defined functions
TriggersnoCallbacks using the Google Apps Engineyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding 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 replicasMulti-source replication using Paxosyes 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)yes infousing Google Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsone 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.noyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlno

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More resources
Amazon DocumentDBGoogle Cloud DatastoreHazelcastManticore Search
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