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DBMS > Elasticsearch vs. Greenplum vs. Oracle Berkeley DB vs. Sphinx

System Properties Comparison Elasticsearch vs. Greenplum vs. Oracle Berkeley DB vs. Sphinx

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonGreenplum  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 metricAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Widely used in-process key-value storeOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelSearch engineRelational 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
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score8.37
Rank#48  Overall
#30  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/­elasticsearchgreenplum.orgwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsphinxsearch.com
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.greenplum.orgdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsphinxsearch.com/­docs
DeveloperElasticPivotal Software Inc.Oracle infooriginally developed by Sleepycat, which was acquired by OracleSphinx Technologies Inc.
Initial release2010200519942001
Current release8.6, January 20237.0.0, September 202318.1.40, May 20203.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoElastic LicenseOpen Source infoApache 2.0Open Source infocommercial license availableOpen 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 languageJavaC, Java, C++ (depending on the Berkeley DB edition)C++
Server operating systemsAll OS with a Java VMLinuxAIX
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 persistentyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnono
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.noyes infosince Version 4.2yes infoonly with the Berkeley DB XML edition
Secondary indexesyes infoAll search fields are automatically indexedyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageyesyes infoSQL interfaced based on SQLite is availableSQL-like query language (SphinxQL)
APIs and other access methodsJava API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C
Java
Perl
Python
R
.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 proceduresyesyesnono
Triggersyes infoby using the 'percolation' featureyesyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectoryesnono
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, allImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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 integrationnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnono

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More resources
ElasticsearchGreenplumOracle Berkeley DBSphinx
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