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DBMS > Elasticsearch vs. Microsoft Azure Data Explorer vs. Oracle NoSQL vs. Sadas Engine vs. YDB

System Properties Comparison Elasticsearch vs. Microsoft Azure Data Explorer vs. Oracle NoSQL vs. Sadas Engine vs. YDB

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle NoSQL  Xexclude from comparisonSadas Engine  Xexclude from comparisonYDB  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 metricFully managed big data interactive analytics platformA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodesSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelSearch engineRelational DBMS infocolumn orientedDocument store
Key-value store
Relational DBMS
Relational DBMSDocument store
Relational 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
Score3.05
Rank#97  Overall
#17  Document stores
#16  Key-value stores
#50  Relational DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score0.33
Rank#287  Overall
#43  Document stores
#132  Relational DBMS
Websitewww.elastic.co/­elasticsearchazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­nosql/­technologies/­nosqlwww.sadasengine.comgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.htmlwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationydb.tech/­en/­docs
DeveloperElasticMicrosoftOracleSADAS s.r.l.Yandex
Initial release20102019201120062019
Current release8.6, January 2023cloud service with continuous releases24.1, May 20248.0
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)commercial infofree trial version availableOpen Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++
Server operating systemsAll OS with a Java VMhostedLinux
Solaris SPARC/x86
AIX
Linux
Windows
Linux
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentFixed schema with schema-less datatypes (dynamic)Support Fixed schema and Schema-less deployment with the ability to interoperate between them.yesFlexible Schema (defined schema, partial schema, schema free)
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-typesoptionalyesyes
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.noyesnonono
Secondary indexesyes infoAll search fields are automatically indexedall fields are automatically indexedyesyesyes
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statementsyesSQL-like query language (YQL)
APIs and other access methodsJava API
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP API (DynamoDB compatible)
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, Rnonono
Triggersyes infoby using the 'percolation' featureyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Electable source-replica replication per shard. Support distributed global deployment with Multi-region table featurenoneActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop ConnectorSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integrationnono
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 Consistency
Immediate Consistency infodepending on configuration
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoconfigurable infoACID within a storage node (=shard)ACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationnoyes infooff heap cacheyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlAzure Active Directory AuthenticationAccess rights for users and rolesAccess rights for users, groups and roles according to SQL-standardAccess rights defined for Yandex Cloud users

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More resources
ElasticsearchMicrosoft Azure Data ExplorerOracle NoSQLSadas EngineYDB
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