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DBMS > LevelDB vs. Netezza vs. Riak KV vs. Solr

System Properties Comparison LevelDB vs. Netezza vs. Riak KV vs. Solr

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Editorial information provided by DB-Engines
NameLevelDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonRiak KV  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesData warehouse and analytics appliance part of IBM PureSystemsDistributed, fault tolerant key-value storeA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelKey-value storeRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.25
Rank#115  Overall
#19  Key-value stores
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Score41.02
Rank#24  Overall
#3  Search engines
Websitegithub.com/­google/­leveldbwww.ibm.com/­products/­netezzasolr.apache.org
Technical documentationgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdwww.tiot.jp/­riak-docs/­riak/­kv/­latestsolr.apache.org/­resources.html
DeveloperGoogleIBMOpenSource, formerly Basho TechnologiesApache Software Foundation
Initial release2011200020092006
Current release1.23, February 20213.2.0, December 20229.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoBSDcommercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ErlangJava
Server operating systemsIllumos
Linux
OS X
Windows
Linux infoincluded in applianceLinux
OS X
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or datenoyesnoyes infosupports customizable data types and automatic typing
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.nonoyes
Secondary indexesnoyesrestrictedyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoyesnoSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
OLE DB
HTTP API
Native Erlang Interface
Java API
RESTful HTTP/JSON API
Supported programming languagesC++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C++
Fortran
Java
Lua
Perl
Python
R
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 proceduresnoyesErlangJava plugins
Triggersnonoyes infopre-commit hooks and post-commit hooksyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infono "single point of failure"Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationselectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith automatic compression on writesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlnoUsers with fine-grained authorization conceptyes, using Riak Securityyes

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More resources
LevelDBNetezza infoAlso called PureData System for Analytics by IBMRiak KVSolr
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