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DBMS > Kinetica vs. Riak KV vs. Splice Machine vs. YDB

System Properties Comparison Kinetica vs. Riak KV vs. Splice Machine vs. YDB

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonRiak KV  Xexclude from comparisonSplice Machine  Xexclude from comparisonYDB  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsDistributed, fault tolerant key-value storeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMSDocument store
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websitewww.kinetica.comsplicemachine.comgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationdocs.kinetica.comwww.tiot.jp/­riak-docs/­riak/­kv/­latestsplicemachine.com/­how-it-worksydb.tech/­en/­docs
DeveloperKineticaOpenSource, formerly Basho TechnologiesSplice MachineYandex
Initial release2012200920142019
Current release7.1, August 20213.2.0, December 20223.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ErlangJava
Server operating systemsLinuxLinux
OS X
Linux
OS X
Solaris
Windows
Linux
Data schemeyesschema-freeyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesnoyesyes
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.nonono
Secondary indexesyesrestrictedyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesSQL-like query language (YQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP API
Native Erlang Interface
JDBC
Native Spark Datasource
ODBC
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
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
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsErlangyes infoJavano
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infopre-commit hooks and post-commit hooksyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infono "single point of failure"Shared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorMulti-source replication
Source-replica replication
Active-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno infolinks between data sets can be storedyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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.yes infoGPU vRAM or System RAMyesno
User concepts infoAccess controlAccess rights for users and roles on table levelyes, using Riak SecurityAccess rights for users, groups and roles according to SQL-standardAccess rights defined for Yandex Cloud users

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More resources
KineticaRiak KVSplice MachineYDB
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