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DBMS > FeatureBase vs. IRONdb vs. Microsoft Azure Data Explorer vs. PlanetScale vs. RDF4J

System Properties Comparison FeatureBase vs. IRONdb vs. Microsoft Azure Data Explorer vs. PlanetScale vs. RDF4J

Editorial information provided by DB-Engines
NameFeatureBase  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPlanetScale  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully managed big data interactive analytics platformScalable, distributed, serverless MySQL database platform built on top of VitessRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSTime Series DBMSRelational DBMS infocolumn orientedRelational DBMSRDF store
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
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.49
Rank#155  Overall
#72  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websitewww.featurebase.comwww.circonus.com/solutions/time-series-database/azure.microsoft.com/­services/­data-explorerplanetscale.comrdf4j.org
Technical documentationdocs.featurebase.comdocs.circonus.com/irondb/category/getting-starteddocs.microsoft.com/­en-us/­azure/­data-explorerplanetscale.com/­docsrdf4j.org/­documentation
DeveloperMolecula and Pilosa Open Source ContributorsCirconus LLC.MicrosoftPlanetScaleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20172017201920202004
Current release2022, May 2022V0.10.20, January 2018cloud service with continuous releases
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC and C++GoJava
Server operating systemsLinux
macOS
LinuxhostedDocker
Linux
macOS
Linux
OS X
Unix
Windows
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.nonoyes
Secondary indexesnonoall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL queriesSQL-like query language (Circonus Analytics Query Language: CAQL)Kusto Query Language (KQL), SQL subsetyes infowith proprietary extensionsno
APIs and other access methodsgRPC
JDBC
Kafka Connector
ODBC
HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesJava
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
PHP
Python
Server-side scripts infoStored proceduresyes, in LuaYes, possible languages: KQL, Python, Ryes infoproprietary syntaxyes
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeSharding infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesconfigurable replication factor, datacenter awareyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency per node, eventual consistency across nodesEventual Consistency
Immediate Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesnonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonoACID at shard levelACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engineyes
Durability infoSupport for making data persistentyes, using Linux fsyncyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlnoAzure Active Directory AuthenticationUsers with fine-grained authorization concept infono user groups or rolesno

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More resources
FeatureBaseIRONdbMicrosoft Azure Data ExplorerPlanetScaleRDF4J infoformerly known as Sesame
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