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DBMS > Hive vs. Solr vs. Spark SQL vs. Sqrrl vs. Tkrzw

System Properties Comparison Hive vs. Solr vs. Spark SQL vs. Sqrrl vs. Tkrzw

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparisonSqrrl  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopA widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processingAdaptable, secure NoSQL built on Apache AccumuloA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelRelational DBMSSearch engineRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Key-value store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitehive.apache.orgsolr.apache.orgspark.apache.org/­sqlsqrrl.comdbmx.net/­tkrzw
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homesolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoinitially developed by FacebookApache Software FoundationApache Software FoundationAmazon infooriginally Sqrrl Data, Inc.Mikio Hirabayashi
Initial release20122006201420122020
Current release3.1.3, April 20229.6.0, April 20243.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2Open Source infoApache 2.0commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScalaJavaC++
Server operating systemsAll OS with a Java VMAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
LinuxLinux
macOS
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingyesyesno
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.yesnono
Secondary indexesyesyes infoAll search fields are automatically indexednoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSolr Parallel SQL InterfaceSQL-like DML and DDL statementsnono
APIs and other access methodsJDBC
ODBC
Thrift
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC++
Java
PHP
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava pluginsnonono
Triggersnoyes infoUser configurable commands triggered on index changesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreSharding infomaking use of Hadoopnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesnoneselectable replication factor infomaking use of Hadoopnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducespark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingnoAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and rolesyesnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)no

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More resources
HiveSolrSpark SQLSqrrlTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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