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DBMS > ArcadeDB vs. EsgynDB vs. GeoMesa vs. Microsoft Azure Data Explorer

System Properties Comparison ArcadeDB vs. EsgynDB vs. GeoMesa vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameArcadeDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonGeoMesa  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Fully managed big data interactive analytics platform
Primary database modelDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Relational DBMSSpatial DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument 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
Score0.10
Rank#358  Overall
#48  Document stores
#38  Graph DBMS
#52  Key-value stores
#35  Time Series DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitearcadedb.comwww.esgyn.cnwww.geomesa.orgazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.arcadedb.comwww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperArcade DataEsgynCCRi and othersMicrosoft
Initial release2021201520142019
Current releaseSeptember 20215.0.0, May 2024cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache License 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, JavaScala
Server operating systemsAll OS with a Java VMLinuxhosted
Data schemeschema-freeyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyes 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.nononoyes
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query language, no joinsyesnoKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
ADO.NET
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesJavaAll languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresJava Stored ProceduresnoYes, possible languages: KQL, Python, R
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingdepending on storage layerSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication between multi datacentersdepending on storage layeryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistencydepending on storage layerEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes inforelationship in graphsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nodepending on storage layerno
User concepts infoAccess controlfine grained access rights according to SQL-standardyes infodepending on the DBMS used for storageAzure Active Directory Authentication

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More resources
ArcadeDBEsgynDBGeoMesaMicrosoft Azure Data Explorer
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