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DBMS > Netezza vs. Pinecone vs. Stardog vs. SurrealDB

System Properties Comparison Netezza vs. Pinecone vs. Stardog vs. SurrealDB

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPinecone  Xexclude from comparisonStardog  Xexclude from comparisonSurrealDB  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsA managed, cloud-native vector databaseEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationA fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelRelational DBMSVector DBMSGraph DBMS
RDF store
Document store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score3.23
Rank#92  Overall
#2  Vector DBMS
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Score1.02
Rank#190  Overall
#33  Document stores
#18  Graph DBMS
Websitewww.ibm.com/­products/­netezzawww.pinecone.iowww.stardog.comsurrealdb.com
Technical documentationdocs.pinecone.io/­docs/­overviewdocs.stardog.comsurrealdb.com/­docs
DeveloperIBMPinecone Systems, IncStardog-UnionSurrealDB Ltd
Initial release2000201920102022
Current release7.3.0, May 2020v1.5.0, May 2024
License infoCommercial or Open Sourcecommercialcommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentsOpen Source
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 languageJavaRust
Server operating systemsLinux infoincluded in appliancehostedLinux
macOS
Windows
Linux
macOS
Windows
Data schemeyesschema-free and OWL/RDFS-schema supportschema-free
Typing infopredefined data types such as float or dateyesString, Number, 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.nono infoImport/export of XML data possible
Secondary indexesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLyesnoYes, compatible with all major SQL variants through dedicated BI/SQL ServerSQL-like query language
APIs and other access methodsJDBC
ODBC
OLE DB
RESTful HTTP APIGraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
GraphQL
RESTful HTTP API
WebSocket
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
Python.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresyesuser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
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.noyes
User concepts infoAccess controlUsers with fine-grained authorization conceptAccess rights for users and rolesyes, based on authentication and database rules

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

Vector databases
2 June 2023, Matthias Gelbmann

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