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DBMS > Netezza vs. Qdrant vs. Realm vs. Stardog

System Properties Comparison Netezza vs. Qdrant vs. Realm vs. Stardog

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonQdrant  Xexclude from comparisonRealm  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsA high-performance vector database with neural network or semantic-based matchingA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSVector DBMSDocument storeGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score1.16
Rank#175  Overall
#6  Vector DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitewww.ibm.com/­products/­netezzagithub.com/­qdrant/­qdrant
qdrant.tech
realm.iowww.stardog.com
Technical documentationqdrant.tech/­documentationrealm.io/­docsdocs.stardog.com
DeveloperIBMQdrantRealm, acquired by MongoDB in May 2019Stardog-Union
Initial release2000202120142010
Current release7.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Sourcecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
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 languageRustJava
Server operating systemsLinux infoincluded in applianceDocker
Linux
macOS
Windows
Android
Backend: server-less
iOS
Windows
Linux
macOS
Windows
Data schemeyesschema-freeyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesNumbers, Strings, Geo, Booleanyesyes
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.nonono infoImport/export of XML data possible
Secondary indexesyesyes infoKeywords, numberic ranges, geo, full-textyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLyesnonoYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBC
ODBC
OLE DB
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
.Net
Java infowith Android only
Objective-C
React Native
Swift
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyesno inforuns within the applications so server-side scripts are unnecessaryuser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyes infoChange Listenersyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationCollection-level replicationnoneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency, tunable consistencyImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynonoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesyes infoIn-Memory realmyes
User concepts infoAccess controlUsers with fine-grained authorization conceptKey-based authenticationyesAccess rights for users and roles

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More resources
Netezza infoAlso called PureData System for Analytics by IBMQdrantRealmStardog
DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
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Recent citations in the news

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, IBM

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

IBM Brings Back a Netezza, Attacks Yellowbrick
29 June 2020, Datanami

Netezza Performance Server
12 August 2020, IBM

provided by Google News

Open source vector database startup Qdrant raises $28M
23 January 2024, TechCrunch

Qdrant offers managed vector database for hybrid clouds
16 April 2024, InfoWorld

Qdrant Announces an Industry-First Hybrid Cloud Offering For Enterprise AI Applications
16 April 2024, businesswire.com

Qdrant Hybrid Cloud is Now Available for OCI Customers: Managed Vector Search Engine for Data-Sensitive AI ...
16 April 2024, blogs.oracle.com

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17 April 2024, Forbes

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9 June 2020, diginomica

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