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DBMS > Apache Phoenix vs. Drizzle vs. FoundationDB vs. Microsoft Azure Data Explorer vs. Postgres-XL

System Properties Comparison Apache Phoenix vs. Drizzle vs. FoundationDB vs. Microsoft Azure Data Explorer vs. Postgres-XL

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDrizzle  Xexclude from comparisonFoundationDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgres-XL  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Ordered key-value store. Core features are complimented by layers.Fully managed big data interactive analytics platformBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSRelational DBMSDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMS infocolumn orientedRelational DBMS
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
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websitephoenix.apache.orggithub.com/­apple/­foundationdbazure.microsoft.com/­services/­data-explorerwww.postgres-xl.org
Technical documentationphoenix.apache.orgapple.github.io/­foundationdbdocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgres-xl.org/­documentation
DeveloperApache Software FoundationDrizzle project, originally started by Brian AkerFoundationDBMicrosoft
Initial release20142008201320192014 infosince 2012, originally named StormDB
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20197.2.4, September 20126.2.28, November 2020cloud service with continuous releases10 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLOpen Source infoApache 2.0commercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++C
Server operating systemsLinux
Unix
Windows
FreeBSD
Linux
OS X
Linux
OS X
Windows
hostedLinux
macOS
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-free infosome layers support schemasFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesno infosome layers support typingyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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 infoXML type, but no XML query functionality
Secondary indexesyesyesnoall fields are automatically indexedyes
SQL infoSupport of SQLyesyes infowith proprietary extensionssupported in specific SQL layer onlyKusto Query Language (KQL), SQL subsetyes infodistributed, parallel query execution
APIs and other access methodsJDBCJDBCMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C++
Java
PHP
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functionsnoin SQL-layer onlyYes, possible languages: KQL, Python, Ruser defined functions
Triggersnono infohooks for callbacks inside the server can be used.noyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
yesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyLinearizable consistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesin SQL-layer onlynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnoACID infoMVCC
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.yesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
Apache PhoenixDrizzleFoundationDBMicrosoft Azure Data ExplorerPostgres-XL
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