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DBMS > Spark SQL vs. Sphinx vs. Transwarp Hippo vs. XTDB

System Properties Comparison Spark SQL vs. Sphinx vs. Transwarp Hippo vs. XTDB

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonTranswarp Hippo  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databasesCloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasetsA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSSearch engineVector DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.00
Rank#383  Overall
#13  Vector DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websitespark.apache.org/­sqlsphinxsearch.comwww.transwarp.cn/­en/­subproduct/­hippogithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docswww.xtdb.com/­docs
DeveloperApache Software FoundationSphinx Technologies Inc.Juxt Ltd.
Initial release2014200120232019
Current release3.5.0 ( 2.13), September 20233.5.1, February 20231.0, May 20231.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availablecommercialOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++C++Clojure
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS
All OS with a Java 8 (and higher) VM
Linux
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesnoVector, Numeric and Stringyes, extensible-data-notation format
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.nonono
Secondary indexesnoyes infofull-text index on all search fieldsnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (SphinxQL)nolimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
Proprietary protocolRESTful HTTP APIHTTP REST
JDBC
Supported programming languagesJava
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Java
Python
Clojure
Java
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supportedShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlnonoRole based access control and fine grained access rights

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More resources
Spark SQLSphinxTranswarp HippoXTDB infoformerly named Crux
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