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DBMS > Firebolt vs. Hypertable vs. Solr vs. Sphinx vs. Splice Machine

System Properties Comparison Firebolt vs. Hypertable vs. Solr vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameFirebolt  Xexclude from comparisonHypertable  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionHighly scalable cloud data warehouse and analytics product infoForked from ClickhouseAn open source BigTable implementation based on distributed file systems such as HadoopA widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSWide column storeSearch engineSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.73
Rank#140  Overall
#63  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.firebolt.iosolr.apache.orgsphinxsearch.comsplicemachine.com
Technical documentationdocs.firebolt.iosolr.apache.org/­resources.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperFirebolt Analytics Inc.Hypertable Inc.Apache Software FoundationSphinx Technologies Inc.Splice Machine
Initial release20202009200620012014
Current release0.9.8.11, March 20169.6.1, May 20243.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++Java
Server operating systemshostedLinux
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)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or dateyesnoyes infosupports customizable data types and automatic typingnoyes
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.yes
Secondary indexesyesrestricted infoonly exact value or prefix value scansyes infoAll search fields are automatically indexedyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyesnoSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)yes
APIs and other access methods.Net
ODBC
RESTful HTTP API
C++ API
Thrift
Java API
RESTful HTTP/JSON API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
JavaScript (Node.js)
Python
C++
Java
Perl
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoJava pluginsnoyes infoJava
Triggersnonoyes infoUser configurable commands triggered on index changesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerselectable replication factor on file system levelyesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlnoyesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
FireboltHypertableSolrSphinxSplice Machine
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