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DBMS > Elasticsearch vs. Netezza vs. Stardog

System Properties Comparison Elasticsearch vs. Netezza vs. Stardog

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricData warehouse and analytics appliance part of IBM PureSystemsEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelSearch engineRelational DBMSGraph DBMS
RDF store
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score134.78
Rank#7  Overall
#1  Search engines
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score2.05
Rank#129  Overall
#11  Graph DBMS
#6  RDF stores
Websitewww.elastic.co/­elasticsearchwww.ibm.com/­products/­netezzawww.stardog.com
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.stardog.com
DeveloperElasticIBMStardog-Union
Initial release201020002010
Current release8.6, January 20237.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoElastic Licensecommercialcommercial 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 servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsAll OS with a Java VMLinux infoincluded in applianceLinux
macOS
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyes infoAll search fields are automatically indexedyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSQL-like query languageyesYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJava API
RESTful HTTP/JSON API
JDBC
ODBC
OLE DB
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 languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyesyesuser defined functions and aggregates, HTTP Server extensions in Java
Triggersyes infoby using the 'percolation' featurenoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectoryesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynonoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationyes
User concepts infoAccess controlUsers with fine-grained authorization conceptAccess rights for users and roles

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More resources
ElasticsearchNetezza infoAlso called PureData System for Analytics by IBMStardog
DB-Engines blog posts

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3 July 2017, Matthias Gelbmann

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2 March 2016, Paul Andlinger

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Recent citations in the news

Introducing Elasticsearch Vector Database to Azure OpenAI Service On Your Data (Preview)
26 March 2024, GovTech

Elasticsearch Open Inference API Supports Cohere Rerank 3
11 April 2024, Business Wire

ElasticSearch Goes Deep on OpenTelemetry with eBPF Donation
13 March 2024, The New Stack

Elasticsearch Open Inference API Supports Cohere Rerank 3
11 April 2024, WICZ

Mastering Elasticsearch: A Beginner's Guide to Powerful Searches and Precision — Part 1
21 November 2023, Towards Data Science

provided by Google 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

U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
22 March 2023, Business Wire

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

provided by Google News



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