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DBMS > Hive vs. Prometheus vs. Riak KV vs. Splice Machine

System Properties Comparison Hive vs. Prometheus vs. Riak KV vs. Splice Machine

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonPrometheus  Xexclude from comparisonRiak KV  Xexclude from comparisonSplice Machine  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopOpen-source Time Series DBMS and monitoring systemDistributed, fault tolerant key-value storeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSTime Series DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitehive.apache.orgprometheus.iosplicemachine.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homeprometheus.io/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latestsplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoinitially developed by FacebookOpenSource, formerly Basho TechnologiesSplice Machine
Initial release2012201520092014
Current release3.1.3, April 20223.2.0, December 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache version 2, commercial enterprise editionOpen Source infoAGPL 3.0, 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 languageJavaGoErlangJava
Server operating systemsAll OS with a Java VMLinux
Windows
Linux
OS X
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesNumeric data onlynoyes
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 infoImport of XML data possibleno
Secondary indexesyesnorestrictedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes
APIs and other access methodsJDBC
ODBC
Thrift
RESTful HTTP/JSON APIHTTP API
Native Erlang Interface
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC++
Java
PHP
Python
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
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 proceduresyes infouser defined functions and integration of map-reducenoErlangyes infoJava
Triggersnonoyes infopre-commit hooks and post-commit hooksyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infono "single point of failure"Shared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoby Federationselectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.noyes
User concepts infoAccess controlAccess rights for users, groups and rolesnoyes, using Riak SecurityAccess rights for users, groups and roles according to SQL-standard

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