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DBMS > IRONdb vs. Linter vs. Vertica

System Properties Comparison IRONdb vs. Linter vs. Vertica

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Editorial information provided by DB-Engines
NameIRONdb  Xexclude from comparisonLinter  Xexclude from comparisonVertica infoOpenText™ Vertica™  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 simplicityRDBMS for high security requirementsCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelTime Series DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.circonus.com/solutions/time-series-database/linter.ruwww.vertica.com
Technical documentationdocs.circonus.com/irondb/category/getting-startedvertica.com/­documentation
DeveloperCirconus LLC.relex.ruOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201719902005
Current releaseV0.10.20, January 201812.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C and C++C++
Server operating systemsLinuxAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
Data schemeschema-freeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyes infotext, numeric, histogramsyesyes
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.nonono
Secondary indexesnoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query language (Circonus Analytics Query Language: CAQL)yesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsHTTP APIADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes, in Luayes infoproprietary syntax with the possibility to convert from PL/SQLyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesAutomatic, metric affinity per nodenonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter awareSource-replica replicationMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency per node, eventual consistency across nodesImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
IRONdbLinterVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
IRONdbLinterVertica infoOpenText™ Vertica™
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