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DBMS > AgensGraph vs. Heroic vs. InterSystems Caché vs. LeanXcale vs. Microsoft Azure Data Explorer

System Properties Comparison AgensGraph vs. Heroic vs. InterSystems Caché vs. LeanXcale vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonHeroic  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA multi-model DBMS and application serverA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesFully managed big data interactive analytics platform
Primary database modelGraph DBMS
Relational DBMS
Time Series DBMSKey-value store
Object oriented DBMS
Relational DBMS
Key-value store
Relational DBMS
Relational DBMS infocolumn oriented
Secondary database modelsDocument storeDocument 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
Score0.23
Rank#315  Overall
#26  Graph DBMS
#140  Relational DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitebitnine.net/­agensgraphgithub.com/­spotify/­heroicwww.intersystems.com/­products/­cachewww.leanxcale.comazure.microsoft.com/­services/­data-explorer
Technical documentationbitnine.net/­documentationspotify.github.io/­heroicdocs.intersystems.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperBitnine Global Inc.SpotifyInterSystemsLeanXcaleMicrosoft
Initial release20162014199720152019
Current release2.1, December 20182018.1.4, May 2020cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open 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 languageCJava
Server operating systemsLinux
OS X
Windows
AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
hosted
Data schemedepending on used data modelschema-freedepending on used data modelyesFixed 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.nonoyesyes
Secondary indexesyesyes infovia Elasticsearchyesall fields are automatically indexed
SQL infoSupport of SQLyesnoyesyes infothrough Apache DerbyKusto Query Language (KQL), SQL subset
APIs and other access methodsCypher Query Language
JDBC
HQL (Heroic Query Language, a JSON-based language)
HTTP API
.NET Client 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 languagesC
Java
JavaScript
Python
C#
C++
Java
C
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesnoyesYes, possible languages: KQL, Python, R
Triggersnonoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesSource-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 systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDno
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.nonoyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and rolesAzure Active Directory Authentication

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More resources
AgensGraphHeroicInterSystems CachéLeanXcaleMicrosoft Azure Data Explorer
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