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DBMS > FatDB vs. Google Cloud Firestore vs. Sphinx vs. Splice Machine vs. Yaacomo

System Properties Comparison FatDB vs. Google Cloud Firestore vs. Sphinx vs. Splice Machine vs. Yaacomo

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonYaacomo  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Cloud 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.Open source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store
Key-value store
Document storeSearch engineRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.85
Rank#51  Overall
#8  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitefirebase.google.com/­products/­firestoresphinxsearch.comsplicemachine.comyaacomo.com
Technical documentationfirebase.google.com/­docs/­firestoresphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperFatCloudGoogleSphinx Technologies Inc.Splice MachineQ2WEB GmbH
Initial release20122017200120142009
Current release3.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C++Java
Server operating systemsWindowshostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Android
Linux
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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.nono
Secondary indexesyesyesyes infofull-text index on all search fieldsyesyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoSQL-like query language (SphinxQL)yesyes
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
JDBC
ODBC
Supported programming languagesC#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsyes, Firebase Rules & Cloud Functionsnoyes infoJava
Triggersyes infovia applicationsyes, with Cloud Functionsnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationnoneMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesUsing Cloud DataflownoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.noAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
FatDBGoogle Cloud FirestoreSphinxSplice MachineYaacomo
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