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DBMS > LMDB vs. Spark SQL vs. Teradata vs. XTDB

System Properties Comparison LMDB vs. Spark SQL vs. Teradata vs. XTDB

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Editorial information provided by DB-Engines
NameLMDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparisonXTDB infoformerly named Crux  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)A general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelKey-value storeRelational DBMSRelational DBMSDocument store
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
Score0.18
Rank#332  Overall
#46  Document stores
Websitewww.symas.com/­symas-embedded-database-lmdbspark.apache.org/­sqlwww.teradata.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationwww.lmdb.tech/­docspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.comwww.xtdb.com/­docs
DeveloperSymasApache Software FoundationTeradataJuxt Ltd.
Initial release2011201419842019
Current release0.9.32, January 20243.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 20191.19, September 2021
License infoCommercial or Open SourceOpen SourceOpen Source infoApache 2.0commercialOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCScalaClojure
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
hosted
Linux
All OS with a Java 8 (and higher) VM
Linux
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes, extensible-data-notation format
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.nonoyesno
Secondary indexesnonoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infoSQL 2016 + extensionslimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
HTTP REST
JDBC
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
Clojure
Java
Server-side scripts infoStored proceduresnonoyes infoUDFs, stored procedures, table functions in parallelno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark CoreSharding infoHashingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneMulti-source replication
Source-replica replication
yes, each node contains all data
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 integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlnonofine grained access rights according to SQL-standard

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More resources
LMDBSpark SQLTeradataXTDB infoformerly named Crux
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