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DBMS > atoti vs. Heroic vs. InterSystems IRIS vs. LeanXcale vs. Microsoft Azure Data Explorer

System Properties Comparison atoti vs. Heroic vs. InterSystems IRIS vs. LeanXcale vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonHeroic  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilityA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesFully managed big data interactive analytics platform
Primary database modelObject oriented DBMSTime Series DBMSDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Key-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
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score3.54
Rank#84  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websiteatoti.iogithub.com/­spotify/­heroicwww.intersystems.com/­products/­intersystems-iriswww.leanxcale.comazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.atoti.iospotify.github.io/­heroicdocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperActiveViamSpotifyInterSystemsLeanXcaleMicrosoft
Initial release2014201820152019
Current release2023.3, June 2023cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache 2.0commercialcommercialcommercial
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 languageJavaJava
Server operating systemsAIX
Linux
macOS
Ubuntu
Windows
hosted
Data schemeschema-freedepending on used data modelyesFixed schema with schema-less datatypes (dynamic)
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-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.noyesyes
Secondary indexesyes infovia Elasticsearchyesall fields are automatically indexed
SQL infoSupport of SQLMultidimensional Expressions (MDX)noyesyes infothrough Apache DerbyKusto Query Language (KQL), SQL subset
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languages.Net
C++
Java
JavaScript (Node.js)
Python
C
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresPythonnoyesYes, possible languages: KQL, Python, R
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingShardingSharding infoImplicit feature of the cloud service
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.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
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.yesnoyesyesno
User concepts infoAccess controlyesAzure Active Directory Authentication
More information provided by the system vendor
atotiHeroicInterSystems IRISLeanXcaleMicrosoft Azure Data Explorer
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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atotiHeroicInterSystems IRISLeanXcaleMicrosoft Azure Data Explorer
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