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DBMS > Elasticsearch vs. GigaSpaces vs. GridDB vs. Oracle Berkeley DB vs. Sphinx

System Properties Comparison Elasticsearch vs. GigaSpaces vs. GridDB vs. Oracle Berkeley DB vs. Sphinx

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGridDB  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 metricHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsScalable in-memory time series database optimized for IoT and Big DataWidely used in-process key-value storeOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelSearch engineDocument store
Object oriented DBMS infoValues are user defined objects
Time Series 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
Graph DBMS
Search engine
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score134.78
Rank#7  Overall
#1  Search engines
Score1.02
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score2.52
Rank#114  Overall
#20  Key-value stores
#3  Native XML DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Websitewww.elastic.co/­elasticsearchwww.gigaspaces.comgriddb.netwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsphinxsearch.com
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.gigaspaces.com/­latest/­landing.htmldocs.griddb.netdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsphinxsearch.com/­docs
DeveloperElasticGigaspaces TechnologiesToshiba CorporationOracle infooriginally developed by Sleepycat, which was acquired by OracleSphinx Technologies Inc.
Initial release20102000201319942001
Current release8.6, January 202315.5, September 20205.1, August 202218.1.40, May 20203.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoElastic LicenseOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen 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 languageJavaJava, C++, .NetC++C, Java, C++ (depending on the Berkeley DB edition)C++
Server operating systemsAll OS with a Java VMLinux
macOS
Solaris
Windows
LinuxAIX
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 persistentschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampnono
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.nono infoXML can be used for describing objects metadatanoyes infoonly with the Berkeley DB XML edition
Secondary indexesyes infoAll search fields are automatically indexedyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageSQL-99 for query and DML statementsSQL92, SQL-like TQL (Toshiba Query Language)yes infoSQL interfaced based on SQLite is availableSQL-like query language (SphinxQL)
APIs and other access methodsJava API
RESTful HTTP/JSON API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C++
Java
Python
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.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 proceduresyesyesnonono
Triggersyes infoby using the 'percolation' featureyes, event driven architectureyesyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectoryes infoMap-Reduce pattern can be built with XAP task executorsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
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 infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at container levelACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 integrationyesyesyes
User concepts infoAccess controlRole-based access controlAccess rights for users can be defined per databasenono
More information provided by the system vendor
ElasticsearchGigaSpacesGridDBOracle Berkeley DBSphinx
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
ElasticsearchGigaSpacesGridDBOracle Berkeley DBSphinx
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