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DBMS > Atos Standard Common Repository vs. GeoMesa vs. LeanXcale vs. Microsoft Azure Data Explorer

System Properties Comparison Atos Standard Common Repository vs. GeoMesa vs. LeanXcale vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGeoMesa  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesFully managed big data interactive analytics platform
Primary database modelDocument store
Key-value store
Spatial DBMSKey-value store
Relational DBMS
Relational 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
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.geomesa.orgwww.leanxcale.comazure.microsoft.com/­services/­data-explorer
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAtos Convergence CreatorsCCRi and othersLeanXcaleMicrosoft
Initial release2016201420152019
Current release17034.0.5, February 2024cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache License 2.0commercialcommercial
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 languageJavaScala
Server operating systemsLinuxhosted
Data schemeSchema and schema-less with LDAP viewsyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateoptionalyesyes 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.yesnoyes
Secondary indexesyesyesall fields are automatically indexed
SQL infoSupport of SQLnonoyes infothrough Apache DerbyKusto Query Language (KQL), SQL subset
APIs and other access methodsLDAPJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesAll languages with LDAP bindingsC
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, R
Triggersyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisiondepending on storage layerSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesdepending 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 methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationdepending on storage layerImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnoACIDno
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.yesdepending on storage layeryesno
User concepts infoAccess controlLDAP bind authenticationyes infodepending on the DBMS used for storageAzure Active Directory Authentication

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More resources
Atos Standard Common RepositoryGeoMesaLeanXcaleMicrosoft Azure Data Explorer
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