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DBMS > Amazon DocumentDB vs. FatDB vs. Hazelcast vs. Sphinx vs. STSdb

System Properties Comparison Amazon DocumentDB vs. FatDB vs. Hazelcast vs. Sphinx vs. STSdb

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFatDB  Xexclude from comparisonHazelcast  Xexclude from comparisonSphinx  Xexclude from comparisonSTSdb  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA .NET NoSQL DBMS that can integrate with and extend SQL Server.A widely adopted in-memory data gridOpen source search engine for searching in data from different sources, e.g. relational databasesKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelDocument storeDocument store
Key-value store
Key-value storeSearch engineKey-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#132  Overall
#24  Document stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.04
Rank#360  Overall
#52  Key-value stores
Websiteaws.amazon.com/­documentdbhazelcast.comsphinxsearch.comgithub.com/­STSSoft/­STSdb4
Technical documentationaws.amazon.com/­documentdb/­resourceshazelcast.org/­imdg/­docssphinxsearch.com/­docs
DeveloperFatCloudHazelcastSphinx Technologies Inc.STS Soft SC
Initial release20192012200820012011
Current release5.3.6, November 20233.5.1, February 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#JavaC++C#
Server operating systemshostedWindowsAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesnoyes infoprimitive types and user defined types (classes)
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.noyes infothe object must implement a serialization strategy
Secondary indexesyesyesyesyes infofull-text index on all search fieldsno
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerSQL-like query languageSQL-like query language (SphinxQL)no
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible).NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JCache
JPA
Memcached protocol
RESTful HTTP API
Proprietary protocol.NET Client API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
Java
Server-side scripts infoStored proceduresnoyes infovia applicationsyes infoEvent Listeners, Executor Servicesnono
Triggersnoyes infovia applicationsyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication factoryes infoReplicated Mapnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
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 operationsnoone or two-phase-commit; repeatable reads; read commitednono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlAccess rights for users and rolesno infoCan implement custom security layer via applicationsRole-based access controlnono

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More resources
Amazon DocumentDBFatDBHazelcastSphinxSTSdb
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