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DBMS > LevelDB vs. Spark SQL vs. Sphinx vs. ToroDB

System Properties Comparison LevelDB vs. Spark SQL vs. Sphinx vs. ToroDB

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Editorial information provided by DB-Engines
NameLevelDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesSpark 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 databasesA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelKey-value storeRelational DBMSSearch engineDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.35
Rank#111  Overall
#19  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitegithub.com/­google/­leveldbspark.apache.org/­sqlsphinxsearch.comgithub.com/­torodb/­server
Technical documentationgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperGoogleApache Software FoundationSphinx Technologies Inc.8Kdata
Initial release2011201420012016
Current release1.23, February 20213.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoBSDOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC++Java
Server operating systemsIllumos
Linux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
All OS with a Java 7 VM
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyesnoyes infostring, integer, double, boolean, date, object_id
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 indexesnonoyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
Proprietary protocol
Supported programming languagesC++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith automatic compression on writesyesyes 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.no
User concepts infoAccess controlnononoAccess rights for users and roles

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More resources
LevelDBSpark SQLSphinxToroDB
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