InfluxData, the creator of InfluxDB, announced a series of updates to the InfluxDB 3.0 product suite including new deployment options and observability capabilities.
A time series database efficiently handles time-stamped data, making it essential for real-time monitoring and performance optimization of systems, servers, and sensors across various industries. InfluxDB has emerged as one of the leading time series databases with its ability to handle large volumes of time-stamped data.
InfluxDB is designed to be an open-source platform that can manage data in chronological order, which is essential for applications that require context over time such as managing application performance metrics and tracking financial market trends.
In April last year, InfluxData revamped InfluxDB with a 3.0 release. In an interview with Datanami, InfluxData co-founder and CTO Paul Dix explained that the overhaul was driven by the need to support high cardinality data and enhance performance.
Version 3.0 employed the FDAP stack (Flight, DataFusion, Arrow, Parquet) and Apache Iceberg to enhance real-time capabilities, data efficiency, and compatibility with other big data tools. It also offered real-time querying, allowing users to execute queries almost instantly.
Building on these advancements, the rebuilt InfluxDB 3.0 offers enhanced performance with unlimited cardinality, high-speed ingestion, and advanced data compression via native object storage. The new capabilities support high-cardinality use cases, including real-time analytics, observability, and IoT/IIoT.
The performance improvements and optimizations aim to make it more efficient for developers to analyze time series data as their system and application data volumes grow.
With its unlimited cardinality, InfluxDB 3.0 can process columnar data with an unlimited number of values. It also offers improved query scaling and lower latency with any performance degradation. This allows systems and applications to maintain responsiveness, even when managing high-cardinality data.
“Intelligent, real-time systems require an operational database capable of managing high-speed, high-resolution workloads,” said Evan Kaplan, CEO of InfluxData. “InfluxDB 3.0 is engineered to meet this challenge head-on with industry-leading ingest performance, unlimited data cardinality, and exceptionally low latency querying, giving architects and developers tools to build real-time monitoring and control systems.”
In addition to InfluxDB 3.0, the company unveiled InfluxDB Clustered, a self-managed version of its time series database, and InfluxDB Cloud Dedicated, its fully managed database-as-a-service offering.
While InfluxDB offers a serverless database offering on AWS for customers who need a pay-as-you-go model, the company’s dedicated solutions, such as InfluxDB Cloud Dedicated and InfluxDB Clustered, are preferred by clients who use time series data.
The dedicated options offer fixed-rate pricing based on the number of virtual machines and amount of data stored, more suited for applications that require continuous, high-performance data handling at predictable pricing.
The InfluxDB Cloud now features an enhanced operational dashboard for better visual monitoring of dedicated clusters’ performance and health. It also has a single-sign-on (SSO) integration for seamless access, new APIs for management, and token handling for automated administrative tasks such as managing users, databases, and tokens within the InfluxDB Cloud Dedicated cluster.
InfluxDB Clustered, which has now transitioned from beta to general availability, is optimized for Kubernetes, offering improved query capabilities and scalable ingest. It also supports new Helm Charts for easier deployment. With this GA release, customers can benefit from all the latest performance enhancements introduced in the InfluxDB 3.0 core.
“The high performance of InfluxDB Clustered enables us to ingest this data immediately upon landing, compress it efficiently, and meet our data retention requirements while keeping storage costs down,” said Kevin Carosso, Software Engineering Lead at Joby Aviation, a current InfluxDB 3.0 customer.
InfluxDB is reportedly working on more granular access control, including query filtering by key-value pairs and refined write permissions. Additionally, the platform is working on integrating with the Apache Iceberg open-source data lake table specification.
Related Items
InfluxData Touts Massive Performance Boost for On-Prem Time-Series Database
Dremio Unveils New Features to Enhance Apache Iceberg Data Lakehouse Performance
Crunchy Data Brings Iceberg to Managed Postgres
Source link
lol
