September 2016 Summaries

In this weekly post, we recap the most interesting InfluxDB and TICK-stack related issues, workarounds, and tips on limiting series in a database, continuous query configuration, and the FILL() function within the continuous query results. To limit the number of series per database, you can set the `max-series-per-database` configuration setting to a desired value, which defaults to 1,000,000. Continuous queries support using an offset interval to alter their execution time, allowing for more flexible scheduling. The FILL() function is used in continuous queries with the RESAMPLE clause and fills data-less intervals with a specified value if at least one data point falls within the FOR interval. Additionally, InfluxDB provides various resources for users, including FAQs, free consultations, virtual training seminars, and support options.

Kapacitor, a monitoring and alerting tool for time series data, has been made available on InfluxData's cloud platform, offering a fully managed instance starting at $200 per month. Existing and new customers can now use Kapacitor's API to create and enable TICKscripts that send alerts based on various criteria such as CPU utilization, moving averages, and outliers. The tool is designed to perform checks every 10 seconds, allowing for real-time monitoring of time series data. With the integration with InfluxDB Cloud, users can access a range of features including alerts, Grafana, and more.

InfluxDB has made significant announcements in the last week, including the launch of InfluxDB Enterprise, which allows for clustering on infrastructure and rebalancing nodes. The company also raised $16 million in funding led by Battery Ventures. InfluxDB was shown to be 27x faster than MongoDB for time-series workloads. Additionally, Kapacitor 1.0 and Telegraf 1.0 were released, providing a data processing engine and plugin-driven agent for collecting metrics, respectively. Various customers have shared their success stories with InfluxDB, including Aiven, BadShark, and browserup, highlighting its performance and scalability in managing time-series data. The company is also hosting several webinars and training sessions, including free events on continuous queries and retention policies, as well as performance tuning and schema design.

Sorting timestamps in query results can be achieved by appending `ORDER BY time DESC` to the query, which returns points with the newest timestamps first. When quoting measurements in line protocol, it is essential to double quote the measurement name and escape the double quotes that are part of the measurement name, as InfluxDB assumes they are part of the measurement name. This helps avoid incorrect results and ensures accurate querying.

Silicon ANGLE | Battery Ventures leads $16M round into time-series DB startup InfluxData` The company, InfluxData, has received a significant investment of $16 million in funding to support its development and growth. This investment was led by Silicon ANGLE and Battery Ventures, two prominent venture capital firms. The funding is aimed at addressing the challenges of analyzing unstructured data generated by connected devices and systems. By solving these operational challenges, InfluxData aims to provide a solution for managing time-series data that can help organizations make more informed decisions about their operations.

InfluxData has raised $16 million in Series B funding led by Battery Ventures to develop its InfluxDB time series database, which helps organize IoT data. The company's goal is to make it easier for businesses to collect, manage and analyze large amounts of data from various sources. With this funding, InfluxData plans to expand its product offerings and improve the scalability and performance of its platform. The investment from Battery Ventures will help InfluxData accelerate its growth and further develop its technology to meet the increasing demand for IoT data management solutions.

InfluxData, a company behind the popular open-source data management platform, InfluxDB, has raised $16 million in Series B funding. The investment was led by Battery Ventures with participation from Mayfield, Trinity Ventures and Bloomberg Beta.

The company, InfluxData, has raised $16M in new funding led by Battery Ventures, following the successful release of its 1.0 version of the TICK stack and InfluxDB Enterprise product. The additional capital will be used to continue developing and expanding the platform, as well as to expand its reach and develop relevant open source applications. The round was led by Dharmesh Thakker, an experienced open source investor who saw the potential for high growth in the time-series data category due to IoT and Dev-Ops tooling demand. InfluxData is pleased to have earned Dharmesh's confidence and has a new board member, while also thanking its existing investors for their participation and insight. The company plans to use the funding to further define the rapidly expanding time-series data market and build a successful business that its employees, customers, community, and investors can be proud of.

InfluxData, a company behind an open-source time-series data platform called InfluxDB, has secured $16 million in Series B financing led by Battery Ventures, with existing investors Mayfield, Trinity Ventures, and Bloomberg Beta also participating. The funding comes as the company releases its 1.0 version of InfluxDB and makes its commercial clustering product generally available. InfluxData's data platform is designed to manage time-series data, which is used in various applications such as IoT, real-time analytics, and custom monitoring, and has already gained traction with companies like Cisco, eBay, and Telefonica. The company plans to use the funds to expand its sales and marketing efforts and develop new products to better serve its community members and enterprise customers. With time-series data emerging as a distinct data-management category, InfluxData is poised to capitalize on the growing demand for its platform.

InfluxDB has released its 1.0 version, which is 27x faster than MongoDB for time-series workloads. The company also announced the release of Kapacitor and Telegraf, two new data processing engines and agents, respectively. InfluxDB Enterprise is now available, allowing users to cluster their databases on their infrastructure with a user-friendly UI. Various companies, including browserup, Aiven, and BadShark, have praised InfluxDB for its performance and ease of use in managing time-series data. The company is also offering free webinars and training sessions, as well as a hoodie giveaway to users who feature their application or product on the InfluxDB website.

InfluxData, a developer of time-series data management software, has raised $16 million in its Series B funding round. The company will use the funds to further develop and commercialize its product, InfluxDB, which is used by companies such as Netflix, Twitter, and Airbnb. InfluxData also plans to expand its sales and marketing efforts to increase its market share. With this funding, the company aims to position itself as a leader in the time-series data management space.

InfluxData has raised $16M in Series B funding to further develop its open-source platform for managing time-series data.` The company is based in San Francisco, CA and aims to provide a scalable solution for handling large datasets.

In this post, the author shares tips on managing unwanted series in InfluxDB, writing to non-DEFAULT retention policies using the CLI, and binding parameters for better security in the HTTP API. The author provides detailed documentation and examples to help users navigate these features of InfluxDB and improve their database management skills.

InfluxDB has released version 1.0, which is 27x faster than MongoDB for time-series workloads. The company also announced the release of Kapacitor 1.0 and Telegraf 1.0, a data processing engine and plugin-driven agent for collecting metrics, respectively. InfluxDB Enterprise is now available, offering clustering capabilities on infrastructure with rebalancing nodes and a user-friendly UI. Several companies, including Project Sherlock, Nanometrics Apollo Server, and DreamHost, have adopted InfluxDB for its scalability and performance in handling time-series data and real-time analytics. To support users, InfluxDB offers free webinars and training sessions, as well as sponsorship opportunities for meetups and events.

InfluxDB 1.0`, a time-series database, has been released by `InfluxData Inc.` as open source software. The new version was developed over nearly three years and marks an important milestone for the company. It is designed to provide fast data ingestion and processing capabilities, making it suitable for high-performance applications. With its release, InfluxDB 1.0 aims to fill a gap in the market for a robust and scalable time-series database solution. The open-source nature of the software allows developers to contribute to its development and use it freely for personal or commercial projects.

InfluxDB 1.0, the open source time series database, has been released after nearly three years of development. The release marks a significant milestone for the company and its users, with tens of thousands of organizations worldwide relying on InfluxDB to manage their time-series data across various industries such as network infrastructure, security, container infrastructure, agriculture, scientific experiments, user analytics, business intelligence, home automation, and more. The database was initially conceived in 2013 while working on a SaaS application called Errplane, which aimed to provide real-time metrics and monitoring. Over the years, InfluxDB has evolved through various iterations, including the development of new open-source projects such as Telegraf, Kapacitor, and Chronograf. The 1.0 release brings stability and compatibility guarantees for the API and storage format, with plans to continue iterating on improvements in future releases. Users can expect continued work on solving limitations such as high cardinality, intelligent rules for automatic rollups, and query language functionality like performing calculations across multiple measurements.

Telegraf 1.0 has been released, marking a significant milestone in the project's journey since its inception nearly two years ago when there were only 18 input plugins and one output plugin available. The new release includes over 80 input plugins and 18 output plugins, with nearly 40 features or enhancements added and more than 45 bugfixes since the previous version. Three notable community contributions include a new SNMP plugin, a webhooks plugin that allows multiple services to run on a single port, and support for being installed as a Windows Service. The next steps include deploying Telegraf on cloud platforms, running it on servers, and sharing user stories of its success, with various incentives offered to encourage adoption.

Kapacitor 1.0 is the latest version of a data processing engine for InfluxDB, which has undergone significant improvements since its initial release in mid-2016, with 33 new features and 42 bug fixes added to date. The new features include HTTP-based subscriptions, template tasks, Holt-Winters forecasting, alert reset expressions, group by fields, Telegram alerting, improved lambda expressions, and live replays, which enhance data processing capabilities and simplify data transport. Beyond 1.0, Kapacitor is planned to receive improvements to alert management, UDF snapshots, and more powerful algorithms, with API endpoints for querying alert states and revamped snapshots for easy model saving and restoration.