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DBMS > LeanXcale vs. Linter vs. Splice Machine

System Properties Comparison LeanXcale vs. Linter vs. Splice Machine

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Editorial information provided by DB-Engines
NameLeanXcale  Xexclude from comparisonLinter  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesRDBMS for high security requirementsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.35
Rank#283  Overall
#41  Key-value stores
#128  Relational DBMS
Score0.10
Rank#350  Overall
#153  Relational DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitewww.leanxcale.comlinter.rusplicemachine.com
Technical documentationsplicemachine.com/­how-it-works
DeveloperLeanXcalerelex.ruSplice Machine
Initial release201519902014
Current release3.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++Java
Server operating systemsAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
OS X
Solaris
Windows
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.no
Secondary indexesyesyes
SQL infoSupport of SQLyes infothrough Apache Derbyyesyes
APIs and other access methodsJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
Java
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoproprietary syntax with the possibility to convert from PL/SQLyes infoJava
Triggersyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
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.yesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
LeanXcaleLinterSplice Machine
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