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DBMS > Elasticsearch vs. Graph Engine vs. Microsoft Azure Data Explorer vs. Milvus vs. YDB

System Properties Comparison Elasticsearch vs. Graph Engine vs. Microsoft Azure Data Explorer vs. Milvus vs. YDB

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMilvus  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 metricA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineFully managed big data interactive analytics platformA DBMS designed for efficient storage of vector data and vector similarity searchesA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelSearch engineGraph DBMS
Key-value store
Relational DBMS infocolumn orientedVector 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
Score135.35
Rank#7  Overall
#1  Search engines
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websitewww.elastic.co/­elasticsearchwww.graphengine.ioazure.microsoft.com/­services/­data-explorermilvus.iogithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlwww.graphengine.io/­docs/­manualdocs.microsoft.com/­en-us/­azure/­data-explorermilvus.io/­docs/­overview.mdydb.tech/­en/­docs
DeveloperElasticMicrosoftMicrosoftYandex
Initial release20102010201920192019
Current release8.6, January 2023cloud service with continuous releases2.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoElastic LicenseOpen Source infoMIT LicensecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageJava.NET and CC++, Go
Server operating systemsAll OS with a Java VM.NEThostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesFixed schema with schema-less datatypes (dynamic)Flexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesVector, Numeric and 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.nonoyesnono
Secondary indexesyes infoAll search fields are automatically indexedall fields are automatically indexednoyes
SQL infoSupport of SQLSQL-like query languagenoKusto Query Language (KQL), SQL subsetnoSQL-like query language (YQL)
APIs and other access methodsJava API
RESTful HTTP/JSON API
RESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIRESTful HTTP API (DynamoDB compatible)
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#
C++
F#
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresyesyesYes, possible languages: KQL, Python, Rnono
Triggersyes infoby using the 'percolation' featurenoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding 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.Active-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop ConnectorSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
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
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationyesnoyesno
User concepts infoAccess controlAzure Active Directory AuthenticationRole based access control and fine grained access rightsAccess rights defined for Yandex Cloud users
More information provided by the system vendor
ElasticsearchGraph Engine infoformer name: TrinityMicrosoft Azure Data ExplorerMilvusYDB
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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More resources
ElasticsearchGraph Engine infoformer name: TrinityMicrosoft Azure Data ExplorerMilvusYDB
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