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

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

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonGridDB  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSphinx  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionHigh 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 databasesAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelDocument 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 engineVector DBMS
Secondary database modelsGraph DBMS
Search engine
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitewww.gigaspaces.comgriddb.netwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsphinxsearch.comgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.griddb.netdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsphinxsearch.com/­docsweaviate.io/­developers/­weaviate
DeveloperGigaspaces TechnologiesToshiba CorporationOracle infooriginally developed by Sleepycat, which was acquired by OracleSphinx Technologies Inc.Weaviate B.V.
Initial release20002013199420012019
Current release15.5, September 20205.1, August 202218.1.40, May 20203.5.1, February 20231.19, May 2023
License infoCommercial or Open SourceOpen 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 availableOpen Source infocommercial license available with Weaviate Enterprise
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 languageJava, C++, .NetC++C, Java, C++ (depending on the Berkeley DB edition)C++Go
Server operating systemsLinux
macOS
Solaris
Windows
LinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyesyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampnonoyes infostring, int, float, geo point, date, cross reference, fuzzy references
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.no infoXML can be used for describing objects metadatanoyes infoonly with the Berkeley DB XML editionno
Secondary indexesyesyesyesyes infofull-text index on all search fieldsyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLSQL-99 for query and DML statementsSQL92, SQL-like TQL (Toshiba Query Language)yes infoSQL interfaced based on SQLite is availableSQL-like query language (SphinxQL)GraphQL is used as query language
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Proprietary protocolGraphQL query language
RESTful HTTP/JSON API
Supported programming languages.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
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresyesnononono
Triggersyes, event driven architectureyesyes infoonly for the SQL APInono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replicationSource-replica replicationnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency within container, eventual consistency across containersEventual Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.yesyesyesyes
User concepts infoAccess controlRole-based access controlAccess rights for users can be defined per databasenonoAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
GigaSpacesGridDBOracle Berkeley DBSphinxWeaviate
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Flexible deployment - Free, open source or fully-managed cloud vector database service...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
As a database supporting the development of generative AI and semantic search applications...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
All companies that have data. ​
» more
Market metricsGitHub trending repository
» more
As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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More resources
GigaSpacesGridDBOracle Berkeley DBSphinxWeaviate
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