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DBMS > GigaSpaces vs. Microsoft Azure Table Storage vs. Postgres-XL vs. Qdrant

System Properties Comparison GigaSpaces vs. Microsoft Azure Table Storage vs. Postgres-XL vs. Qdrant

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Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonPostgres-XL  Xexclude from comparisonQdrant  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA Wide Column Store for rapid development using massive semi-structured datasetsBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresA high-performance vector database with neural network or semantic-based matching
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Wide column storeRelational DBMSVector DBMS
Secondary database modelsGraph DBMS
Search engine
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score1.28
Rank#167  Overall
#8  Vector DBMS
Websitewww.gigaspaces.comazure.microsoft.com/­en-us/­services/­storage/­tableswww.postgres-xl.orggithub.com/­qdrant/­qdrant
qdrant.tech
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlwww.postgres-xl.org/­documentationqdrant.tech/­documentation
DeveloperGigaspaces TechnologiesMicrosoftQdrant
Initial release200020122014 infosince 2012, originally named StormDB2021
Current release15.5, September 202010 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen Source infoMozilla public licenseOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetCRust
Server operating systemsLinux
macOS
Solaris
Windows
hostedLinux
macOS
Docker
Linux
macOS
Windows
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesNumbers, Strings, Geo, Boolean
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 infoXML type, but no XML query functionalityno
Secondary indexesyesnoyesyes infoKeywords, numberic ranges, geo, full-text
SQL infoSupport of SQLSQL-99 for query and DML statementsnoyes infodistributed, parallel query executionno
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
RESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Supported programming languages.Net
C++
Java
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresyesnouser defined functions
Triggersyes, event driven architecturenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Collection-level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyImmediate ConsistencyEventual Consistency, tunable consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingACID infoMVCC
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.yesnonoyes
User concepts infoAccess controlRole-based access controlAccess rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standardKey-based authentication

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More resources
GigaSpacesMicrosoft Azure Table StoragePostgres-XLQdrant
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