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DBMS > IRONdb vs. Microsoft Azure Table Storage vs. Solr vs. Sqrrl

System Properties Comparison IRONdb vs. Microsoft Azure Table Storage vs. Solr vs. Sqrrl

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Editorial information provided by DB-Engines
NameIRONdb  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSolr  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.
DescriptionA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA Wide Column Store for rapid development using massive semi-structured datasetsA widely used distributed, scalable search engine based on Apache LuceneAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelTime Series DBMSWide column storeSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#315  Overall
#28  Time Series DBMS
Score5.77
Rank#66  Overall
#5  Wide column stores
Score51.62
Rank#20  Overall
#3  Search engines
Websitewww.circonus.com/­solutions/­time-series-databaseazure.microsoft.com/­en-us/­services/­storage/­tableslucene.apache.org/­solrsqrrl.com
Technical documentationdocs.circonus.com/­irondblucene.apache.org/­solr/­resources.html
DeveloperCirconus LLC.MicrosoftApache Software FoundationAmazon infooriginally Sqrrl Data, Inc.
Initial release2017201220062012
Current releaseV0.10.20, January 20188.6.2, September 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2commercial
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.
Implementation languageC and C++JavaJava
Server operating systemsLinuxhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeschema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
Typing infopredefined data types such as float or dateyes infotext, numeric, histogramsyesyes infosupports customizable data types and automatic typingyes
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 indexesnonoyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query language (Circonus Analytics Query Language: CAQL)noSolr Parallel SQL Interfaceno
APIs and other access methodsHTTP APIRESTful HTTP APIJava API
RESTful HTTP/JSON API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
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
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyes, in LuanoJava pluginsno
Triggersnonoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesAutomatic, metric affinity per nodeSharding infoImplicit feature of the cloud serviceShardingSharding infomaking use of Hadoop
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.yesselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency per node, eventual consistency across nodesImmediate ConsistencyEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingoptimistic lockingAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlnoAccess rights based on private key authentication or shared access signaturesyesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)
More information provided by the system vendor
IRONdbMicrosoft Azure Table StorageSolrSqrrl
Specific characteristicsIRONdb is a highly available, distributed Time Series Database. It can support dozens...
» more
Competitive advantagesUnmatched Scalability IRONdb is unique among TSDBs in that it does not use a consensus...
» more
Typical application scenariosReal Systems Monitoring Monitor your systems infrastructure in real time across thousands...
» more
Key customersIRONdb serves the needs of the world's largest Time Series Database customers. One...
» more
Market metricsOnly TSDB capable of scaling to billions of metrics. Only TSDB to scale to dozens...
» more
Licensing and pricing modelsIRONdb is licensed under a subscription model based on the number of active metrics...
» more

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IRONdbMicrosoft Azure Table StorageSolrSqrrl
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