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DBMS > Elasticsearch vs. Kinetica vs. Microsoft Azure Data Explorer vs. NebulaGraph vs. Tkrzw

System Properties Comparison Elasticsearch vs. Kinetica vs. Microsoft Azure Data Explorer vs. NebulaGraph vs. Tkrzw

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNebulaGraph  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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 vectorized database across both GPUs and CPUsFully managed big data interactive analytics platformA distributed, linear scalable, high perfomant Graph DBMSA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelSearch engineRelational DBMSRelational DBMS infocolumn orientedGraph DBMSKey-value store
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Spatial DBMS
Time Series 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
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score2.23
Rank#116  Overall
#10  Graph DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.elastic.co/­elasticsearchwww.kinetica.comazure.microsoft.com/­services/­data-explorergithub.com/­vesoft-inc/­nebula
www.nebula-graph.io
dbmx.net/­tkrzw
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.nebula-graph.io
DeveloperElasticKineticaMicrosoftVesoft Inc.Mikio Hirabayashi
Initial release20102012201920192020
Current release8.6, January 20237.1, August 2021cloud service with continuous releases0.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialcommercialOpen Source infoApache Version 2.0 + Common Clause 1.0Open Source infoApache Version 2.0
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.
Implementation languageJavaC, C++C++C++
Server operating systemsAll OS with a Java VMLinuxhostedLinuxLinux
macOS
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesFixed schema with schema-less datatypes (dynamic)Strong typed schemaschema-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-typesyesno
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 indexedyesall fields are automatically indexedyes infoNebula Graph internally uses the Key-Value store RocksDB for persistency. The vertices, edges, and their properties are stored as Key while their values are stored as Value. The primary indexes are per Key and secondary indexes are per Value.
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetSQL-like query languageno
APIs and other access methodsJava API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Browser interface
console (shell)
Cypher Query Language
GO Object Graph Mapper
Java Object Graph Mapper
NGBatis infoORM framework for NebulaGraph and Spring-Boot
Proprietary native API
Python Object Graph Mapper
Query language nGQL
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C++
Go
Java
PHP
Python
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyesuser defined functionsYes, possible languages: KQL, Python, Ruser defined functionsno
Triggersyes infoby using the 'percolation' featureyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Causal Clustering using Raft protocolnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop ConnectornoSpark 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, allImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infousing RocksDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationyes infoGPU vRAM or System RAMnoyesyes infousing specific database classes
User concepts infoAccess controlAccess rights for users and roles on table levelAzure Active Directory AuthenticationRole-based access controlno
More information provided by the system vendor
ElasticsearchKineticaMicrosoft Azure Data ExplorerNebulaGraphTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsNebulaGraph is a truly distributed, linearly scalable, lightning-fast graph database,...
» more
Competitive advantagesNebulaGraph boasts the world's only graph database solution that is able to host...
» more
Typical application scenariosSocial networking Fraud detection Knowledge graph Data warehouse management Anti...
» more
Key customersCompanies from a variety of industries have implemented NebulaGraph Database in production,...
» more
Market metricsAt our very early stage, NebulaGraph has already received over 10,000 stars on GitHub...
» more
Licensing and pricing modelsNebulaGraph is open source and free to use under Apache 2.0 license.
» more

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More resources
ElasticsearchKineticaMicrosoft Azure Data ExplorerNebulaGraphTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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