DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Elasticsearch vs. Microsoft Azure Data Explorer vs. NSDb vs. Trafodion

System Properties Comparison Elasticsearch vs. Microsoft Azure Data Explorer vs. NSDb vs. Trafodion

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNSDb  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
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 metricFully managed big data interactive analytics platformScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesTransactional SQL-on-Hadoop DBMS
Primary database modelSearch engineRelational DBMS infocolumn orientedTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score132.83
Rank#7  Overall
#1  Search engines
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Websitewww.elastic.co/­elasticsearchazure.microsoft.com/­services/­data-explorernsdb.iotrafodion.apache.org
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorernsdb.io/­Architecturetrafodion.apache.org/­documentation.html
DeveloperElasticMicrosoftApache Software Foundation, originally developed by HP
Initial release2010201920172014
Current release8.6, January 2023cloud service with continuous releases2.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialOpen Source infoApache Version 2.0Open Source infoApache 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 languageJavaJava, ScalaC++, Java
Server operating systemsAll OS with a Java VMhostedLinux
macOS
Linux
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes: int, bigint, decimal, stringyes
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.noyesnono
Secondary indexesyes infoAll search fields are automatically indexedall fields are automatically indexedall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetSQL-like query languageyes
APIs and other access methodsJava API
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
gRPC
HTTP REST
WebSocket
ADO.NET
JDBC
ODBC
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, RnoJava Stored Procedures
Triggersyes infoby using the 'percolation' featureyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop ConnectorSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes infovia user defined functions and HBase
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, allEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationnono
User concepts infoAccess controlAzure Active Directory Authenticationfine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
ElasticsearchMicrosoft Azure Data ExplorerNSDbTrafodion
DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2017
2 January 2018, Paul Andlinger, Matthias Gelbmann

Elasticsearch moved into the top 10 most popular database management systems
3 July 2017, Matthias Gelbmann

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB?
5 June 2024, hackernoon.com

8 Powerful Alternatives to Elasticsearch
25 April 2024, Yahoo Finance

Splunk vs Elasticsearch | A Comparison and How to Choose
12 January 2024, SentinelOne

Introducing Elasticsearch Vector Database to Azure OpenAI Service On Your Data (Preview)
26 March 2024, insider.govtech.com

Netflix Uses Elasticsearch Percolate Queries to Implement Reverse Searches Efficiently
29 April 2024, InfoQ.com

provided by Google News

We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer | Azure updates
31 May 2024, azure.microsoft.com

Update records in a Kusto Database (public preview) | Azure updates
20 February 2024, azure.microsoft.com

Public Preview: Azure Data Explorer connector for Apache Flink | Azure updates
8 January 2024, azure.microsoft.com

Announcing General Availability to migrate Virtual Network injected Azure Data Explorer Cluster to Private Endpoints ...
5 February 2024, azure.microsoft.com

New Features for graph-match KQL Operator: Enhanced Pattern Matching and Cycle Control | Azure updates
24 January 2024, azure.microsoft.com

provided by Google News

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here