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DBMS > LMDB vs. Spark SQL vs. Teradata vs. Valentina Server

System Properties Comparison LMDB vs. Spark SQL vs. Teradata vs. Valentina Server

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Editorial information provided by DB-Engines
NameLMDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionA high performant, light-weight, embedded key-value database librarySpark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)Object-relational database and reports server
Primary database modelKey-value storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#121  Overall
#20  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Score0.21
Rank#325  Overall
#144  Relational DBMS
Websitewww.symas.com/­symas-embedded-database-lmdbspark.apache.org/­sqlwww.teradata.comwww.valentina-db.net
Technical documentationwww.lmdb.tech/­docspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.comvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperSymasApache Software FoundationTeradataParadigma Software
Initial release2011201419841999
Current release0.9.32, January 20243.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 20195.7.5
License infoCommercial or Open SourceOpen SourceOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCScala
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
hosted
Linux
Linux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nonoyes
Secondary indexesnonoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infoSQL 2016 + extensionsyes
APIs and other access methodsJDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
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
Java
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnonoyes infoUDFs, stored procedures, table functions in parallelyes
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneMulti-source replication
Source-replica replication
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 integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlnonofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
LMDBSpark SQLTeradataValentina Server
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