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DBMS > GridGain vs. Qdrant vs. Spark SQL vs. STSdb

System Properties Comparison GridGain vs. Qdrant vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonQdrant  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteA high-performance vector database with neural network or semantic-based matchingSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelKey-value store
Relational DBMS
Vector DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score1.28
Rank#167  Overall
#8  Vector DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitewww.gridgain.comgithub.com/­qdrant/­qdrant
qdrant.tech
spark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationwww.gridgain.com/­docs/­index.htmlqdrant.tech/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGridGain Systems, Inc.QdrantApache Software FoundationSTS Soft SC
Initial release2007202120142011
Current releaseGridGain 8.5.13.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetRustScalaC#
Server operating systemsLinux
OS X
Solaris
Windows
Docker
Linux
macOS
Windows
Linux
OS X
Windows
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesNumbers, Strings, Geo, Booleanyesyes infoprimitive types and user defined types (classes)
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.yesnono
Secondary indexesyesyes infoKeywords, numberic ranges, geo, full-textnono
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnoSQL-like DML and DDL statementsno
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
JDBC
ODBC
.NET Client API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)nono
Triggersyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Collection-level replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency, tunable consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlSecurity Hooks for custom implementationsKey-based authenticationnono

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More resources
GridGainQdrantSpark SQLSTSdb
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