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DBMS > IRONdb vs. Microsoft Azure Data Explorer vs. RDF4J vs. SingleStore

System Properties Comparison IRONdb vs. Microsoft Azure Data Explorer vs. RDF4J vs. SingleStore

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Editorial information provided by DB-Engines
NameIRONdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully managed big data interactive analytics platformRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type
Primary database modelTime Series DBMSRelational DBMS infocolumn orientedRDF storeRelational 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
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.82
Rank#65  Overall
#37  Relational DBMS
Score0.72
Rank#234  Overall
#9  RDF stores
Score6.03
Rank#62  Overall
#35  Relational DBMS
Websitewww.circonus.com/solutions/time-series-database/azure.microsoft.com/­services/­data-explorerrdf4j.orgwww.singlestore.com
Technical documentationdocs.circonus.com/irondb/category/getting-starteddocs.microsoft.com/­en-us/­azure/­data-explorerrdf4j.org/­documentationdocs.singlestore.com
DeveloperCirconus LLC.MicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.SingleStore Inc.
Initial release2017201920042013
Current releaseV0.10.20, January 2018cloud service with continuous releases8.5, January 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageC and C++JavaC++, Go
Server operating systemsLinuxhostedLinux
OS X
Unix
Windows
Linux info64 bit version required
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyes 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.noyesno
Secondary indexesnoall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-like query language (Circonus Analytics Query Language: CAQL)Kusto Query Language (KQL), SQL subsetnoyes infobut no triggers and foreign keys
APIs and other access methodsHTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languages.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
Java
PHP
Python
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes, in LuaYes, possible languages: KQL, Python, Ryesyes
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesAutomatic, metric affinity per nodeSharding infoImplicit feature of the cloud servicenoneSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter awareyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency per node, eventual consistency across nodesEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlnoAzure Active Directory AuthenticationnoFine grained access control via users, groups and roles
More information provided by the system vendor
IRONdbMicrosoft Azure Data ExplorerRDF4J infoformerly known as SesameSingleStore infoformer name was MemSQL
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more

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More resources
IRONdbMicrosoft Azure Data ExplorerRDF4J infoformerly known as SesameSingleStore infoformer name was MemSQL
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