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DBMS > Amazon DocumentDB vs. Google Cloud Firestore vs. RRDtool vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Google Cloud Firestore vs. RRDtool vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonRRDtool  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeDocument storeTime Series DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score7.85
Rank#51  Overall
#8  Document stores
Score1.87
Rank#136  Overall
#11  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbfirebase.google.com/­products/­firestoreoss.oetiker.ch/­rrdtoolsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesfirebase.google.com/­docs/­firestoreoss.oetiker.ch/­rrdtool/­docsphinxsearch.com/­docs
DeveloperGoogleTobias OetikerSphinx Technologies Inc.
Initial release2019201719992001
Current release1.8.0, 20223.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL V2 and FLOSSOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC infoImplementations in Java (e.g. RRD4J) and C# availableC++
Server operating systemshostedhostedHP-UX
Linux
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesNumeric data onlyno
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.nonono infoExporting into and restoring from XML files possible
Secondary indexesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnononoSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
in-process shared library
Pipes
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionsnono
Triggersnoyes, with Cloud Functionsnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding 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 replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Using Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistencynone
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 operationsyesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoby using the rrdcached daemonyes
Durability infoSupport for making data persistentyesyesyesyes 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
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.nono

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More resources
Amazon DocumentDBGoogle Cloud FirestoreRRDtoolSphinx
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