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DBMS > LMDB vs. Microsoft Azure AI Search vs. OrigoDB vs. Spark SQL

System Properties Comparison LMDB vs. Microsoft Azure AI Search vs. OrigoDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameLMDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA high performant, light-weight, embedded key-value database librarySearch-as-a-service for web and mobile app developmentA fully ACID in-memory object graph databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeSearch engineDocument store
Object oriented DBMS
Relational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.99
Rank#125  Overall
#21  Key-value stores
Score5.59
Rank#63  Overall
#7  Search engines
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.symas.com/­symas-embedded-database-lmdbazure.microsoft.com/­en-us/­services/­searchorigodb.comspark.apache.org/­sql
Technical documentationwww.lmdb.tech/­doclearn.microsoft.com/­en-us/­azure/­searchorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSymasMicrosoftRobert Friberg et alApache Software Foundation
Initial release201120152009 infounder the name LiveDB2014
Current release0.9.32, January 2024V13.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen SourcecommercialOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC#Scala
Server operating systemsLinux
Unix
Windows
hostedLinux
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesUser defined using .NET types and collectionsyes
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 infocan be achieved using .NETno
Secondary indexesnoyesyesno
SQL infoSupport of SQLnononoSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP API.NET Client API
HTTP API
LINQ
JDBC
ODBC
Supported programming languages.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
C#
Java
JavaScript
Python
.NetJava
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesno
Triggersnonoyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoImplicit feature of the cloud serviceSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlnoyes infousing Azure authenticationRole based authorizationno

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More resources
LMDBMicrosoft Azure AI SearchOrigoDBSpark SQL
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