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DBMS > Elasticsearch vs. HugeGraph vs. mSQL vs. Oracle Berkeley DB vs. Sphinx

System Properties Comparison Elasticsearch vs. HugeGraph vs. mSQL vs. Oracle Berkeley DB vs. Sphinx

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonHugeGraph  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricA fast-speed and highly-scalable Graph DBMSmSQL (Mini SQL) is a simple and lightweight RDBMSWidely used in-process key-value storeOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelSearch engineGraph DBMSRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Search engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.elastic.co/­elasticsearchgithub.com/­hugegraph
hugegraph.apache.org
hughestech.com.au/­products/­msqlwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsphinxsearch.com
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlhugegraph.apache.org/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsphinxsearch.com/­docs
DeveloperElasticBaiduHughes TechnologiesOracle infooriginally developed by Sleepycat, which was acquired by OracleSphinx Technologies Inc.
Initial release20102018199419942001
Current release8.6, January 20230.94.4, October 202118.1.40, May 20203.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoElastic LicenseOpen Source infoApache Version 2.0commercial infofree licenses can be providedOpen Source infocommercial license availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaCC, Java, C++ (depending on the Berkeley DB edition)C++
Server operating systemsAll OS with a Java VMLinux
macOS
Unix
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnono
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.nononoyes infoonly with the Berkeley DB XML edition
Secondary indexesyes infoAll search fields are automatically indexedyes infoalso supports composite index and range indexyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languagenoA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersyes infoSQL interfaced based on SQLite is availableSQL-like query language (SphinxQL)
APIs and other access methodsJava API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
ODBC
Proprietary protocol
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Groovy
Java
Python
C
C++
Delphi
Java
Perl
PHP
Tcl
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesasynchronous Gremlin script jobsnonono
Triggersyes infoby using the 'percolation' featurenonoyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBasenonenoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infodepending on used storage backend, e.g. Cassandra and HBasenoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectorvia hugegraph-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allEventual Consistencynone
Foreign keys infoReferential integritynoyes infoedges in graphnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesnoyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.Memcached and Redis integrationyesnoyes
User concepts infoAccess controlUsers, roles and permissionsnonono

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More resources
ElasticsearchHugeGraphmSQL infoMini SQLOracle Berkeley DBSphinx
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