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DBMS > Elasticsearch vs. GridDB vs. Ignite vs. JaguarDB vs. Microsoft Azure Data Explorer

System Properties Comparison Elasticsearch vs. GridDB vs. Ignite vs. JaguarDB vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonGridDB  Xexclude from comparisonIgnite  Xexclude from comparisonJaguarDB  Xexclude from comparisonMicrosoft Azure Data Explorer  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 metricScalable in-memory time series database optimized for IoT and Big DataApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Performant, highly scalable DBMS for AI and IoT applicationsFully managed big data interactive analytics platform
Primary database modelSearch engineTime Series DBMSKey-value store
Relational DBMS
Key-value store
Vector DBMS
Relational DBMS infocolumn oriented
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Key-value store
Relational 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
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitewww.elastic.co/­elasticsearchgriddb.netignite.apache.orgwww.jaguardb.comazure.microsoft.com/­services/­data-explorer
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.griddb.netapacheignite.readme.io/­docswww.jaguardb.com/­support.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperElasticToshiba CorporationApache Software FoundationDataJaguar, Inc.Microsoft
Initial release20102013201520152019
Current release8.6, January 20235.1, August 2022Apache Ignite 2.63.3 July 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoElastic LicenseOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0Open Source infoGPL V3.0commercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++, Java, .NetC++ infothe server part. Clients available in other languages
Server operating systemsAll OS with a Java VMLinuxLinux
OS X
Solaris
Windows
Linuxhosted
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.nonoyesnoyes
Secondary indexesyes infoAll search fields are automatically indexedyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageSQL92, SQL-like TQL (Toshiba Query Language)ANSI-99 for query and DML statements, subset of DDLA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersKusto Query Language (KQL), SQL subset
APIs and other access methodsJava API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesnoyes (compute grid and cache interceptors can be used instead)noYes, possible languages: KQL, Python, R
Triggersyes infoby using the 'percolation' featureyesyes (cache interceptors and events)noyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes (replicated cache)Multi-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop ConnectorConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes (compute grid and hadoop accelerator)noSpark connector (open source): github.com/­Azure/­azure-kusto-spark
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 within container, eventual consistency across containersImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACIDnono
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 integrationyesyesnono
User concepts infoAccess controlAccess rights for users can be defined per databaseSecurity Hooks for custom implementationsrights management via user accountsAzure Active Directory Authentication
More information provided by the system vendor
ElasticsearchGridDBIgniteJaguarDBMicrosoft Azure Data Explorer
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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ElasticsearchGridDBIgniteJaguarDBMicrosoft Azure Data Explorer
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