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DBMS > Google Cloud Firestore vs. Ignite vs. Spark SQL vs. Sphinx vs. Tkrzw

System Properties Comparison Google Cloud Firestore vs. Ignite vs. Spark SQL vs. Sphinx vs. Tkrzw

Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonIgnite  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionCloud 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.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Spark 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 databasesA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument storeKey-value store
Relational DBMS
Relational DBMSSearch engineKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.96
Rank#48  Overall
#8  Document stores
Score3.64
Rank#89  Overall
#13  Key-value stores
#48  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score0.09
Rank#354  Overall
#51  Key-value stores
Websitefirebase.google.com/­products/­firestoreignite.apache.orgspark.apache.org/­sqlsphinxsearch.comdbmx.net/­tkrzw
Technical documentationfirebase.google.com/­docs/­firestoreapacheignite.readme.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperGoogleApache Software FoundationApache Software FoundationSphinx Technologies Inc.Mikio Hirabayashi
Initial release20172015201420012020
Current releaseApache Ignite 2.63.5.0 ( 2.13), September 20233.5.1, February 20230.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, .NetScalaC++C++
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS
Data schemeschema-freeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesnono
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.noyesnono
Secondary indexesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsSQL-like query language (SphinxQL)no
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Proprietary protocol
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C#
C++
Java
PHP
Python
Ruby
Scala
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud Functionsyes (compute grid and cache interceptors can be used instead)nonono
Triggersyes, with Cloud Functionsyes (cache interceptors and events)nonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes (replicated cache)nonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflowyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDnono
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.yesnoyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Security Hooks for custom implementationsnonono

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More resources
Google Cloud FirestoreIgniteSpark SQLSphinxTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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