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

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

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGreptimeDB  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.An open source Time Series DBMS built for increased scalability, high performance and efficiencySpark 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 storeTime Series 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
Score0.12
Rank#351  Overall
#34  Time Series 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-databasegreptime.comspark.apache.org/­sqlsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesfirebase.google.com/­docs/­databasedocs.greptime.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperGoogle infoacquired by Google 2014Greptime Inc.Apache Software FoundationSphinx Technologies Inc.
Initial release20192012202220142001
Current release3.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open 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 languageRustScalaC++
Server operating systemshostedhostedAndroid
Docker
FreeBSD
Linux
macOS
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-free, schema definition possibleyesyes
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
gRPC
HTTP API
JDBC
JDBC
ODBC
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Java
JavaScript
Objective-C
C++
Erlang
Go
Java
JavaScript
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'Pythonnono
TriggersnoCallbacks are triggered when data changesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, 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 replicasnonenone
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 possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsyesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.no
User concepts infoAccess controlAccess rights for users and rolesyes, based on authentication and database rulesSimple rights management via user accountsnono
More information provided by the system vendor
Amazon DocumentDBFirebase Realtime DatabaseGreptimeDBSpark SQLSphinx
Specific characteristicsGreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more
Competitive advantages- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more
Typical application scenariosFor IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more
Key customersGreptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more
Market metricsGreptimeDB has garnered global recognition by topping GitHub trends following its...
» more
Licensing and pricing modelsGreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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Amazon DocumentDBFirebase Realtime DatabaseGreptimeDBSpark SQLSphinx
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