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DBMS > Apache Phoenix vs. Heroic vs. Ingres vs. LeanXcale vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Phoenix vs. Heroic vs. Ingres vs. LeanXcale vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonHeroic  Xexclude from comparisonIngres  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchWell established RDBMSA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesFully managed big data interactive analytics platform
Primary database modelRelational DBMSTime Series DBMSRelational 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
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitephoenix.apache.orggithub.com/­spotify/­heroicwww.actian.com/­databases/­ingreswww.leanxcale.comazure.microsoft.com/­services/­data-explorer
Technical documentationphoenix.apache.orgspotify.github.io/­heroicdocs.actian.com/­ingresdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationSpotifyActian CorporationLeanXcaleMicrosoft
Initial release201420141974 infooriginally developed at University Berkely in early 1970s20152019
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201911.2, May 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC
Server operating systemsLinux
Unix
Windows
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hosted
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-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.nonono infobut tools for importing/exporting data from/to XML-files availableyes
Secondary indexesyesyes infovia Elasticsearchyesall fields are automatically indexed
SQL infoSupport of SQLyesnoyesyes infothrough Apache DerbyKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBCHQL (Heroic Query Language, a JSON-based language)
HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functionsnoyesYes, 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 nodesShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesIngres Replicatoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyesyes
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.yesnonoyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
Apache PhoenixHeroicIngresLeanXcaleMicrosoft Azure Data Explorer
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