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DBMS > LeanXcale vs. Spark SQL vs. Teradata

System Properties Comparison LeanXcale vs. Spark SQL vs. Teradata

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Editorial information provided by DB-Engines
NameLeanXcale  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesSpark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelKey-value store
Relational DBMS
Relational 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
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitewww.leanxcale.comspark.apache.org/­sqlwww.teradata.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.com
DeveloperLeanXcaleApache Software FoundationTeradata
Initial release201520141984
Current release3.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScala
Server operating systemsLinux
OS X
Windows
hosted
Linux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyes
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.noyes
Secondary indexesnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLyes infothrough Apache DerbySQL-like DML and DDL statementsyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC
Java
Scala
Java
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnoyes infoUDFs, stored procedures, table functions in parallel
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
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 persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standard

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More resources
LeanXcaleSpark SQLTeradata
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