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IRONdb System Properties

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Editorial information provided by DB-Engines
DescriptionA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity
Primary database modelTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Rank#317  Overall
#29  Time Series DBMS
Technical documentationdocs.circonus.com/­irondb
DeveloperCirconus LLC.
Initial release2017
Current releaseV0.10.20, January 2018
License infoCommercial or Open Sourcecommercial
Cloud-based only infoOnly available as a cloud serviceno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++
Server operating systemsLinux
Data schemeschema-free
Typing infopredefined data types such as float or dateyes infotext, numeric, histograms
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.no
Secondary indexesno
SQL infoSupport of SQLSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsHTTP API
Supported programming languages.Net
JavaScript (Node.js)
Server-side scripts infoStored proceduresyes, in Lua
Partitioning methods infoMethods for storing different data on different nodesAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano
Concurrency infoSupport for concurrent manipulation of datayes
Durability infoSupport for making data persistentyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlno
More information provided by the system vendor
Specific characteristics

IRONdb is a highly available, distributed Time Series Database. It can support dozens of nodes per availability zone, and ingest billions of metrics per second. IRONdb is one of the highest performing TSDBs due to the highly optimized C and Assembly implementation.

IRONdb can act as a remote storage destination for Prometheus, and integrate with the Grafana visualization tool. Data can be analyzed with the CAQL (Circonus Analytics Query Language) functional language, which provides a wide range of statistical and numeric analytical capabilities.

IRONdb was developed by Circonus, and is the underlying TSDB behind the Circonus.

Competitive advantages

Unmatched Scalability

IRONdb is unique among TSDBs in that it does not use a consensus algorithm for distributed operations. Rather, it relies on operations being commutative in nature, so that data may be applied to any node in any order. This approach avoids the difficult technical problems inherent to distributed systems which require consensus algorithms to operate, and the reliability issues that come with them. As a result, IRONdb can operate with far more nodes than other solutions, and still remain highly performant. Installations with dozens of nodes per availability zone are standard, and operate with no single point of failure.

Unmatched Performance

IRONdb is written in C and Assembly for optimal performance. By minimizing memory allocations, and avoiding copying data wherever possible, IRONdb is able to achieve significant runtime performance over other solutions. Additionally, IRONdb is optimized for a minimum memory footprint per node through the use of highly optimized data structures, allowing each node to handle many more metrics per node than other solutions.

Unmatched Operational Efficiency and Data Safety

IRONdb was designed such that it can be operated without any bespoke administrator skillsets. Standard Linux administration knowledge is sufficient to get IRONdb up and running and accomplish standard node maintenance operations. You don't need a domain specialist with hard to find skills, or a large team of operators.

IRONdb is capable of operating with data replicated in upwards of 4 different availability zones for survivability in double fault loss scenarios. Additionally, IRONdb supports the ZFS filesystem, to take advantage of the unique data safety features offered there such as block checksumming and bitrot detection.

Typical application scenarios

Real Systems Monitoring

Monitor your systems infrastructure in real time across thousands of hosts. IRONdb is capable of ingesting tens of thousands of metrics per host across tens of thousands of hosts. Additionally, because IRONdb is capable of ingesting histogram based metrics, it can easily handle billions of metrics per second from APIs and third party integrations.

IoT Systems Monitoring

IRONdb is uniquely suited to fulfill the telemetry needs of large scale Internet of Things systems. IRONdb's stream tags and histogram based data structures are optimized for the ephemeral nature of these systems which generate high frequency metrics with high cardinality metadata. These characteristics also lend IRONdb to be exceptionally suited for industrial scale device monitoring.

Key customers

IRONdb serves the needs of the world's largest Time Series Database customers. One customer, Xandr, uses IRONdb to ingest and analyze nearly half a billion metrics per minute.

Market metrics

Only TSDB capable of scaling to billions of metrics.

Only TSDB to scale to dozens of nodes across multiple availability zones.

Only TSDB to store histogram based data.

Highest performing Time Series Database.

Licensing and pricing models

IRONdb is licensed under a subscription model based on the number of active metrics in a given time window.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Recent citations in the news

Circonus Announces Availability of Spring 2020 Release
21 April 2020, PRNewswire

Bob Moul's latest gig is leading data intelligence company Circonus
30 October 2019, Technical.ly

Database Heterogeneity Helps Address IoT Analytics Challenges
22 September 2020, IoT World Today

On the Radar: COVID-19, Circonus, and Fake FB Accounts
4 March 2020, Datanami

Circonus Launches the First Machine Data Intelligence Platform Built to Harness the Exploding Volume of Data in a World with a Trillion Connected Computers
29 October 2019, PRNewswire

provided by Google News

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