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DBMS > LeanXcale vs. Riak TS vs. Splice Machine

System Properties Comparison LeanXcale vs. Riak TS vs. Splice Machine

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Editorial information provided by DB-Engines
NameLeanXcale  Xexclude from comparisonRiak TS  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KVOpen-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
Time Series DBMSRelational 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
Score0.25
Rank#308  Overall
#26  Time Series DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitewww.leanxcale.comsplicemachine.com
Technical documentationwww.tiot.jp/­riak-docs/­riak/­ts/­latestsplicemachine.com/­how-it-works
DeveloperLeanXcaleOpen Source, formerly Basho TechnologiesSplice Machine
Initial release201520152014
Current release3.0.0, September 20223.1, March 2021
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangJava
Server operating systemsLinux
OS X
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or datenoyes
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 indexesrestrictedyes
SQL infoSupport of SQLyes infothrough Apache Derbyyes, limitedyes
APIs and other access methodsJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
HTTP API
Native Erlang Interface
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
Java
Scala
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresErlangyes infoJava
Triggersyes infopre-commit hooks and post-commit hooksyes
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno infolinks between datasets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
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 controlnoAccess rights for users, groups and roles according to SQL-standard

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More resources
LeanXcaleRiak TSSplice Machine
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