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DBMS > EsgynDB vs. Oracle Coherence vs. Spark SQL vs. Sphinx

System Properties Comparison EsgynDB vs. Oracle Coherence vs. Spark SQL vs. Sphinx

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonOracle Coherence  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionOracles in-memory data grid solutionSpark 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 databases
Primary database modelRelational DBMSKey-value storeRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score1.97
Rank#129  Overall
#22  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.esgyn.cnwww.oracle.com/­java/­coherencespark.apache.org/­sqlsphinxsearch.com
Technical documentationdocs.oracle.com/­en/­middleware/­standalone/­coherencespark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperEsgynOracleApache Software FoundationSphinx Technologies Inc.
Initial release2015200720142001
Current release14.1, August 20233.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJavaScalaC++
Server operating systemsLinuxAll OS with a Java VMLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesnonoyes infofull-text index on all search fields
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
ODBC
JCache
JPA
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C++
Java
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresJava Stored Proceduresnonono
Triggersnoyes infoLive Eventsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyes, with selectable consistency levelnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDconfigurablenono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infooptionallyyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardauthentification to access the cache via certificates or http basic authenticationnono

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EsgynDBOracle CoherenceSpark SQLSphinx
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