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DBMS > FatDB vs. Google BigQuery vs. JaguarDB vs. Microsoft Azure Table Storage vs. Sphinx

System Properties Comparison FatDB vs. Google BigQuery vs. JaguarDB vs. Microsoft Azure Table Storage vs. Sphinx

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonJaguarDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSphinx  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Large scale data warehouse service with append-only tablesPerformant, highly scalable DBMS for AI and IoT applicationsA Wide Column Store for rapid development using massive semi-structured datasetsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Key-value store
Relational DBMSKey-value store
Vector DBMS
Wide column storeSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score5.98
Rank#56  Overall
#5  Search engines
Websitecloud.google.com/­bigquerywww.jaguardb.comazure.microsoft.com/­en-us/­services/­storage/­tablessphinxsearch.com
Technical documentationcloud.google.com/­bigquery/­docswww.jaguardb.com/­support.htmlsphinxsearch.com/­docs
DeveloperFatCloudGoogleDataJaguar, Inc.MicrosoftSphinx Technologies Inc.
Initial release20122010201520122001
Current release3.3 July 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL V3.0commercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C++ infothe server part. Clients available in other languagesC++
Server operating systemsWindowshostedLinuxhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyesschema-freeyes
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.nonono
Secondary indexesyesnoyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLno infoVia inetgration in SQL ServeryesA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersnoSQL-like query language (SphinxQL)
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
RESTful HTTP/JSON APIJDBC
ODBC
RESTful HTTP APIProprietary protocol
Supported programming languagesC#.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes infovia applicationsuser defined functions infoin JavaScriptnonono
Triggersyes infovia applicationsnononono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoSince BigQuery is designed for querying datanooptimistic lockingno
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.nonono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)rights management via user accountsAccess rights based on private key authentication or shared access signaturesno

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More resources
FatDBGoogle BigQueryJaguarDBMicrosoft Azure Table StorageSphinx
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