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DBMS > Apache Phoenix vs. ArcadeDB vs. CouchDB vs. InfinityDB vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Phoenix vs. ArcadeDB vs. CouchDB vs. InfinityDB vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonArcadeDB  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonInfinityDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.A Java embedded Key-Value Store which extends the Java Map interfaceFully managed big data interactive analytics platform
Primary database modelRelational DBMSDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Document storeKey-value storeRelational DBMS infocolumn oriented
Secondary database modelsSpatial DBMS infousing the Geocouch extensionDocument 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
Score0.10
Rank#358  Overall
#48  Document stores
#38  Graph DBMS
#52  Key-value stores
#35  Time Series DBMS
Score8.30
Rank#47  Overall
#7  Document stores
Score0.08
Rank#365  Overall
#55  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitephoenix.apache.orgarcadedb.comcouchdb.apache.orgboilerbay.comazure.microsoft.com/­services/­data-explorer
Technical documentationphoenix.apache.orgdocs.arcadedb.comdocs.couchdb.org/­en/­stableboilerbay.com/­infinitydb/­manualdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationArcade DataApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerBoiler Bay Inc.Microsoft
Initial release20142021200520022019
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019September 20213.3.3, December 20234.0cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaErlangJava
Server operating systemsLinux
Unix
Windows
All OS with a Java VMAndroid
BSD
Linux
OS X
Solaris
Windows
All OS with a Java VMhosted
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesnoyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes 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.nonononoyes
Secondary indexesyesyesyes infovia viewsno infomanual creation possible, using inversions based on multi-value capabilityall fields are automatically indexed
SQL infoSupport of SQLyesSQL-like query language, no joinsnonoKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBCJDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
RESTful HTTP/JSON APIAccess via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
JavaC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
Java.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functionsView functions in JavaScriptnoYes, possible languages: KQL, Python, R
Triggersnoyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoimproved architecture with release 2.0noneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationMulti-source replication
Source-replica replication
noneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes inforelationship in graphsnono infomanual creation possible, using inversions based on multi-value capabilityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno infoatomic operations within a single document possibleACID infoOptimistic locking for transactions; no isolation for bulk loadsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infostrategy: optimistic lockingyesyes
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.yesnonono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users can be defined per databasenoAzure Active Directory Authentication

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Apache PhoenixArcadeDBCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"InfinityDBMicrosoft Azure Data Explorer
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