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DBMS > Apache Phoenix vs. EsgynDB vs. Hawkular Metrics vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Phoenix vs. EsgynDB vs. Hawkular Metrics vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonEsgynDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Fully managed big data interactive analytics platform
Primary database modelRelational DBMSRelational DBMSTime Series 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
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitephoenix.apache.orgwww.esgyn.cnwww.hawkular.orgazure.microsoft.com/­services/­data-explorer
Technical documentationphoenix.apache.orgwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationEsgynCommunity supported by Red HatMicrosoft
Initial release2014201520142019
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 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++, JavaJava
Server operating systemsLinux
Unix
Windows
LinuxLinux
OS X
Windows
hosted
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeFixed 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 indexesyesyesnoall fields are automatically indexed
SQL infoSupport of SQLyesyesnoKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBCADO.NET
JDBC
ODBC
HTTP RESTMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
All languages supporting JDBC/ODBC/ADO.NetGo
Java
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functionsJava Stored ProceduresnoYes, possible languages: KQL, Python, R
Triggersnonoyes infovia Hawkular Alertingyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on CassandraSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication between multi datacentersselectable replication factor infobased on Cassandrayes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
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.yesnonono
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-standardnoAzure Active Directory Authentication

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More resources
Apache PhoenixEsgynDBHawkular MetricsMicrosoft Azure Data Explorer
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