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DBMS > HEAVY.AI vs. Riak KV vs. Solr vs. SpatiaLite

System Properties Comparison HEAVY.AI vs. Riak KV vs. Solr vs. SpatiaLite

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonRiak KV  Xexclude from comparisonSolr  Xexclude from comparisonSpatiaLite  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareDistributed, fault tolerant key-value storeA widely used distributed, scalable search engine based on Apache LuceneSpatial extension of SQLite
Primary database modelRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesSearch engineSpatial DBMS
Secondary database modelsSpatial DBMSSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.10
Rank#126  Overall
#61  Relational DBMS
Score4.44
Rank#80  Overall
#9  Key-value stores
Score44.28
Rank#24  Overall
#3  Search engines
Score1.72
Rank#149  Overall
#3  Spatial DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
solr.apache.orgwww.gaia-gis.it/­fossil/­libspatialite/­index
Technical documentationdocs.heavy.aiwww.tiot.jp/­riak-docs/­riak/­kv/­latestsolr.apache.org/­resources.htmlwww.gaia-gis.it/­gaia-sins/­spatialite_topics.html
DeveloperHEAVY.AI, Inc.OpenSource, formerly Basho TechnologiesApache Software FoundationAlessandro Furieri
Initial release2016200920062008
Current release5.10, January 20223.2.0, December 20229.5.0, February 20245.0.0, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache version 2, commercial enterprise editionOpen Source infoApache Version 2Open Source infoMPL 1.1, GPL v2.0 or LGPL v2.1
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDAErlangJavaC++
Server operating systemsLinuxLinux
OS X
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)server-less
Data schemeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesnoyes infosupports customizable data types and automatic typingyes
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.nonoyesno
Secondary indexesnorestrictedyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyesnoSolr Parallel SQL Interfaceyes
APIs and other access methodsJDBC
ODBC
Thrift
Vega
HTTP API
Native Erlang Interface
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
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
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoErlangJava pluginsno
Triggersnoyes infopre-commit hooks and post-commit hooksyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinSharding infono "single point of failure"Shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationselectable replication factoryesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynono infolinks between data sets can be storednoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyes, using Riak Securityyesno

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Riak KVSolrSpatiaLite
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