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DBMS > GridDB vs. GridGain vs. Qdrant vs. Sphinx

System Properties Comparison GridDB vs. GridGain vs. Qdrant vs. Sphinx

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonGridGain  Xexclude from comparisonQdrant  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataGridGain is an in-memory computing platform, built on Apache IgniteA high-performance vector database with neural network or semantic-based matchingOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Vector DBMSSearch engine
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score1.28
Rank#167  Overall
#7  Vector DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitegriddb.netwww.gridgain.comgithub.com/­qdrant/­qdrant
qdrant.tech
sphinxsearch.com
Technical documentationdocs.griddb.netwww.gridgain.com/­docs/­index.htmlqdrant.tech/­documentationsphinxsearch.com/­docs
DeveloperToshiba CorporationGridGain Systems, Inc.QdrantSphinx Technologies Inc.
Initial release2013200720212001
Current release5.1, August 2022GridGain 8.5.13.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoApache Version 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++Java, C++, .NetRustC++
Server operating systemsLinuxLinux
OS X
Solaris
Windows
Docker
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesNumbers, Strings, Geo, Booleanno
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.noyesno
Secondary indexesyesyesyes infoKeywords, numberic ranges, geo, full-textyes infofull-text index on all search fields
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)ANSI-99 for query and DML statements, subset of DDLnoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Proprietary protocol
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)no
Triggersyesyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes (replicated cache)Collection-level replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual Consistency, tunable consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDno
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.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlAccess rights for users can be defined per databaseSecurity Hooks for custom implementationsKey-based authenticationno
More information provided by the system vendor
GridDBGridGainQdrantSphinx
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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GridDBGridGainQdrantSphinx
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