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DBMS > Amazon DocumentDB vs. Firebase Realtime Database vs. NuoDB vs. Spark SQL vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Firebase Realtime Database vs. NuoDB vs. Spark SQL vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonNuoDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.NuoDB is a webscale distributed database that supports SQL and ACID transactionsSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeDocument storeRelational DBMSRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score13.64
Rank#39  Overall
#6  Document stores
Score0.94
Rank#197  Overall
#92  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbfirebase.google.com/­products/­realtime-databasewww.3ds.com/­nuodb-distributed-sql-databasespark.apache.org/­sqlsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesfirebase.google.com/­docs/­databasedoc.nuodb.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperGoogle infoacquired by Google 2014Dassault Systèmes infooriginally NuoDB, Inc.Apache Software FoundationSphinx Technologies Inc.
Initial release20192012201320142001
Current release3.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infolimited edition freeOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC++
Server operating systemshostedhostedhosted infoAmazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nononono
Secondary indexesyesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnonoyesSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Android
iOS
JavaScript API
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Java
JavaScript
Objective-C
.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'Java, SQLnono
TriggersnoCallbacks are triggered when data changesyesnono
Partitioning methods infoMethods for storing different data on different nodesnonedata is dynamically stored/cached on the nodes where it is read/writtenyes, utilizing Spark CoreSharding 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 replicasyes infoManaged transparently by NuoDBnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsyesACID infotunable commit protocolnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoTemporary tableno
User concepts infoAccess controlAccess rights for users and rolesyes, based on authentication and database rulesStandard SQL roles/ privileges, Administrative Usersnono

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More resources
Amazon DocumentDBFirebase Realtime DatabaseNuoDBSpark SQLSphinx
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