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DBMS > Microsoft Access vs. Microsoft Azure AI Search vs. Sphinx vs. TimesTen vs. WakandaDB

System Properties Comparison Microsoft Access vs. Microsoft Azure AI Search vs. Sphinx vs. TimesTen vs. WakandaDB

Editorial information provided by DB-Engines
NameMicrosoft Access  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSphinx  Xexclude from comparisonTimesTen  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Search-as-a-service for web and mobile app developmentOpen source search engine for searching in data from different sources, e.g. relational databasesIn-Memory RDBMS compatible to OracleWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSSearch engineSearch engineRelational DBMSObject oriented DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Score1.31
Rank#163  Overall
#74  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitewww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­en-us/­services/­searchsphinxsearch.comwww.oracle.com/­database/­technologies/­related/­timesten.htmlwakanda.github.io
Technical documentationdeveloper.microsoft.com/­en-us/­accesslearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docsdocs.oracle.com/­database/­timesten-18.1wakanda.github.io/­doc
DeveloperMicrosoftMicrosoftSphinx Technologies Inc.Oracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005Wakanda SAS
Initial release19922015200119982012
Current release1902 (16.0.11328.20222), March 2019V13.5.1, February 202311 Release 2 (11.2.2.8.0)2.7.0 (April 29, 2019), April 2019
License infoCommercial or Open Sourcecommercial infoBundled with Microsoft OfficecommercialOpen Source infoGPL version 2, commercial licence availablecommercialOpen Source infoAGPLv3, extended commercial license available
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++C++, JavaScript
Server operating systemsWindows infoNot a real database server, but making use of DLLshostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
OS X
Windows
Data schemeyesyesyesyesyes
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.nonono
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyes infobut not compliant to any SQL standardnoSQL-like query language (SphinxQL)yesno
APIs and other access methodsADO.NET
DAO
ODBC
OLE DB
RESTful HTTP APIProprietary protocolJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
RESTful HTTP API
Supported programming languagesC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C#
Java
JavaScript
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C++
Java
PL/SQL
JavaScript
Server-side scripts infoStored proceduresyes infosince Access 2010 using the ACE-enginenonoPL/SQLyes
Triggersyes infosince Access 2010 using the ACE-enginenononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supportednonenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoImplicit feature of the cloud servicenoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infobut no files for transaction loggingnonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infobut no files for transaction loggingyesyes infoThe original contents of fields are not stored in the Sphinx index.yes infoby means of logfiles and checkpointsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlno infoa simple user-level security was built in till version Access 2003yes infousing Azure authenticationnofine grained access rights according to SQL-standardyes

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More resources
Microsoft AccessMicrosoft Azure AI SearchSphinxTimesTenWakandaDB
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