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DBMS > Hypertable vs. Solr vs. Spark SQL

System Properties Comparison Hypertable vs. Solr vs. Spark SQL

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopA widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelWide column storeSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score44.28
Rank#24  Overall
#3  Search engines
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitesolr.apache.orgspark.apache.org/­sql
Technical documentationsolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHypertable Inc.Apache Software FoundationApache Software Foundation
Initial release200920062014
Current release0.9.8.11, March 20169.5.0, February 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaScala
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or datenoyes 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.yesno
Secondary indexesrestricted infoonly exact value or prefix value scansyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLnoSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methodsC++ API
Thrift
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoJava pluginsno
Triggersnoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlnoyesno

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More resources
HypertableSolrSpark SQL
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