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DBMS > Microsoft Azure Data Explorer vs. RRDtool vs. Solr vs. SQream DB vs. Sqrrl

System Properties Comparison Microsoft Azure Data Explorer vs. RRDtool vs. Solr vs. SQream DB vs. Sqrrl

Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonRRDtool  Xexclude from comparisonSolr  Xexclude from comparisonSQream DB  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionFully managed big data interactive analytics platformIndustry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.A widely used distributed, scalable search engine based on Apache Lucenea GPU-based, columnar RDBMS for big data analytics workloadsAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMS infocolumn orientedTime Series DBMSSearch engineRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column 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
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.90
Rank#132  Overall
#11  Time Series DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.74
Rank#224  Overall
#103  Relational DBMS
Websiteazure.microsoft.com/­services/­data-exploreross.oetiker.ch/­rrdtoolsolr.apache.orgsqream.comsqrrl.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-exploreross.oetiker.ch/­rrdtool/­docsolr.apache.org/­resources.htmldocs.sqream.com
DeveloperMicrosoftTobias OetikerApache Software FoundationSQream TechnologiesAmazon infooriginally Sqrrl Data, Inc.
Initial release20191999200620172012
Current releasecloud service with continuous releases1.8.0, 20229.6.1, May 20242022.1.6, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoGPL V2 and FLOSSOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC infoImplementations in Java (e.g. RRD4J) and C# availableJavaC++, CUDA, Haskell, Java, ScalaJava
Server operating systemshostedHP-UX
Linux
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)LinuxLinux
Data schemeFixed schema with schema-less datatypes (dynamic)yesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesschema-free
Typing infopredefined data types such as float or dateyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesNumeric data onlyyes infosupports customizable data types and automatic typingyes, ANSI Standard SQL 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.yesno infoExporting into and restoring from XML files possibleyes
Secondary indexesall fields are automatically indexednoyes infoAll search fields are automatically indexednoyes
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetnoSolr Parallel SQL Interfaceyesno
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
in-process shared library
Pipes
Java API
RESTful HTTP/JSON API
.Net
JDBC
ODBC
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, RnoJava pluginsuser defined functions in Pythonno
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes infoUser configurable commands triggered on index changesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicenoneShardinghorizontal and vertical partitioningSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneyesnoneselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
noneEventual ConsistencyImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyes infoby using the rrdcached daemonyesyesyes
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.noyesyes
User concepts infoAccess controlAzure Active Directory AuthenticationnoyesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Microsoft Azure Data ExplorerRRDtoolSolrSQream DBSqrrl
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