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InfluxData

Time-series data platform for real-time analytics

Overview

InfluxData builds InfluxDB, a platform for collecting, storing, and analyzing time-stamped data at any scale. It lets developers query and analyze data in real time to uncover insights and support decision-making. The product works by handling time-series data end-to-end—from collection to storage and real-time querying—across open-source and enterprise editions, with optional support and consulting services under a subscription model. The company differentiates itself through a focused time-series database solution that serves diverse sectors (e.g., finance, IoT, telecommunications) with both free and paid offerings, enabling teams to deploy real-time analytics at scale. The goal is to help organizations gain a competitive edge by turning live data into actionable insights through a scalable, subscription-based platform.

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About InfluxData

Simplify's Rating
Why InfluxData is rated
B-
Rated B on Competitive Edge
Rated B on Growth Potential
Rated C on Differentiation

Industries

Data & AnalyticsEnterprise SoftwareAI & Machine Learning

Company Size

51-200

Company Stage

Series E

Total Funding

$201M

Headquarters

San Francisco, California

Founded

2012

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Simplify's Take

What believers are saying

  • Litmus partnership at Hannover Messe 2026 targets industrial AI and edge telemetry.
  • InfluxDB 3.10 added backup, deletes, RBAC, and Parquet import in June 2026.
  • AWS expanded Timestream for InfluxDB to eight more regions on August 31, 2026.

What critics are saying

  • InfluxDB 3 Core and Enterprise still force migration off legacy TSM products.
  • InfluxData's headcount fell to 198 by March 2026, signaling tighter execution.
  • If InfluxDB 3 adoption stalls, AWS Timestream for InfluxDB owns the platform relationship.

What makes InfluxData unique

  • InfluxDB 3 rebuilt on FDAP, winning recent-data workloads with infinite cardinality.
  • Telegraf Enterprise controls 5 billion-download telemetry fleets across edge and cloud.
  • AWS Timestream for InfluxDB extends InfluxData through managed, multi-region enterprise deployments.

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Funding

Total Funding

$201M

Below

Industry Average

Funded Over

8 Rounds

Series E funding typically includes additional rounds after Series D if the company needs more capital. The business is usually stable, and these rounds are typically used for further expansion or to address market challenges.
Series E Funding Comparison
Below Average

Industry standards

$100M
$245M
$250M
$1.3B
$1.5B

Benefits

Remote-first, work from anywhere environment

Allowance for home office setup or co-working space

10-minute workday company-wide stand-ups to stay connected with our colleagues from around the world!

Fun, remote-friendly events throughout the year such as trivia, paint-alongs, yoga, Meditation Mondays, and many more.

Diversity & Inclusion Counsel with educational events

Paid volunteer time

Work-life balance that is truly a part of our culture

Medical/Dental/Vision – we cover 100% of premiums for you and dependents

Generous company contributions to your FSA or HSA

Mental health programs such as TalkSpace, Headspace and more

Short-Term/Long-Term Disability & Life Insurance

401(k)

Employee Assistance Program

Flexible Time Off policy – and we actually encourage you to use it!

Annual educational budget

Financial planning

Growth & Insights and Company News

Headcount

6 month growth

-2%

1 year growth

-2%

2 year growth

-2%
TechNewsDaily
Oct 1st, 2026
Beginner's guide to InfluxDB's 2026 time-series platform.

Beginner's guide to InfluxDB's 2026 time-series platform. Learn how InfluxDB IOX uses Rust and Apache Arrow to provide unbounded cardinality and query speeds of 1 billion rows per second per core. This guide helps teams migrating from Prometheus or TimescaleDB to manage high-precision event data and metrics. Moving away from Prometheus and TimescaleDB. InfluxDB IOX is the new engine powering InfluxDB Cloud, and it uses Rust and the Apache Arrow ecosystem to process time-series data. Teams that use Prometheus manage a pull-based system optimized for metrics. Prometheus graduated from the CNCF and excels in cloud-native monitoring through built-in service discovery, which helps with scalability. InfluxDB is a push-based system that suits event logs and IoT sensor data. Many teams leave TimescaleDB because they hit scaling walls with compression or struggle to manage data that lacks a time column. InfluxDB IOX addresses these issues through a columnar architecture with Apache Parquet files for on-disk storage. I recommend this platform for teams that need to manage massive amounts of high-precision event data alongside regular metrics. The project began when founders Paul Dix and Todd Persen pivoted from a SaaS company called Errplane to build an open-source database. This move followed an $8.1 million investment from Mayfield and Trinity Ventures. InfluxData later secured $16 million in Series B funding to expand its reach. Prometheus is a pull-based system that requires an application to publish metrics to an endpoint, whereas InfluxDB is a push-based system where the application sends data directly. IOX technical specifications. The IOX engine allows for unbounded cardinality. Users write event data with infinite cardinality and slice data across any dimension without sacrificing performance. The columnar design uses per-column compression, dictionaries, and run length encoding to increase speed. InfluxDB IOX reaches query speeds of 1 billion rows per second per core through partitioning by time and tags. Because the new engine relies on the Apache Arrow ecosystem and DataFusion, users can now connect their time-series data to various third-party tools using standard PostgreSQL drivers instead of having to learn entirely new and proprietary communication protocols. This architecture uses DataFusion as its parser, planner, optimizer, and execution engine. Companies like Nordstrom, eBay, and Solar City use InfluxDB to manage their data, while Mozilla uses the technology to access performance metrics for the Firefox browser in real-time. Engineering implementation and migration. I have seen engineering teams struggle with the steep learning curve of the Flux query language during previous InfluxDB iterations. Version changes often force teams to rebuild their entire visualization stack. You should plan for a shift in how you handle metadata. Previous versions of InfluxDB required many tags to manage metadata, which eventually slowed performance as cardinality grew. InfluxDB IOX removes these cardinality limits, yet you must still account for the change in data architecture. I suggest you evaluate your current data needs before committing to a migration. Prometheus works well if you only need to monitor metrics in a dynamic Kubernetes environment. InfluxDB is a better fit if you need to store high-precision event data from sensors or IoT devices. The IOX engine is a middle ground because it provides SQL capabilities that older versions lacked. You must decide if your team can handle the move from a pull model to a push model. The migration from Prometheus or TimescaleDB to InfluxDB IOX involves more than just changing a database. You will face new ways of handling data retention and shard groups. InfluxDB OSS v2 uses a retention enforcement service that deletes shard groups when they fall outside the bucket retention period. This service runs at intervals you can configure using the storage-retention-check-interval option. I have noticed users complain about the rollercoaster of InfluxDB version changes, specifically the shift from Go to Rust. This transition can feel like rebuilding the entire metric visualization from scratch. You should also consider that TimescaleDB is a PostgreSQL extension, which requires different management than a standalone time-series database like InfluxDB. Does the ability to run SQL queries on high-cardinality event data justify the effort of migrating your existing metric pipelines?

Associated Press
Aug 11th, 2026
InfluxData appoints Satyam Vaghani as CPO to lead InfluxDB 3 expansion

InfluxData, creator of time series database InfluxDB, has appointed Satyam Vaghani as chief product officer. Vaghani will oversee product, engineering, and operations as the company expands adoption of InfluxDB 3. Vaghani brings over 20 years of experience in enterprise infrastructure products. He joins from Tiyaro, an AI infrastructure software company he co-founded and led as CEO. Previously, he served as SVP and general manager of AI and IoT at Nutanix and co-founded PernixData, a flash virtualisation company acquired by Nutanix. He began his career at VMware as principal engineer and storage CTO. InfluxData focuses on time series databases for real-time systems, targeting industrial AI, intelligent infrastructure, and complex time series applications.

InfluxData
Aug 11th, 2026
InfluxData appoints Satyam Vaghani as Chief Product Officer to lead next phase of platform growth.

InfluxData appoints Satyam Vaghani as Chief Product Officer to lead next phase of platform growth. Get the latest on new features, product updates, and what's next for InfluxData Veteran infrastructure executive to lead product and engineering as InfluxData expands adoption of InfluxDB 3 SAN FRANCISCO, August 11, 2026 - InfluxData, creator of the leading time series database InfluxDB(R), today announced the appointment of Satyam Vaghani as Chief Product Officer. Vaghani will lead product, engineering, and operations as the company expands adoption of InfluxDB 3 and advances the database for developers and enterprises building complex time series systems at scale. Vaghani brings more than two decades of experience building enterprise infrastructure products across storage, cloud platforms, edge computing, IoT, and AI, from developing foundational storage technology to founding and leading infrastructure software companies. At InfluxData, he will oversee the next phase of InfluxDB 3, building on the company's long-standing technical leadership in time series as modern systems move beyond monitoring the physical world to understanding and acting on it in real-time. That work will span industrial AI, intelligent infrastructure, and increasingly complex time series applications, shaping the database around the demands of the systems customers are building next. "Industrial AI and autonomous systems are making real-time operational data essential to how the physical world is understood and controlled," said Evan Kaplan, CEO of InfluxData. "InfluxDB gives developers and enterprises the foundation to build those systems with the performance, scale, and reliability they demand. Satyam brings the product vision and technical depth to push InfluxDB 3 further, expand what customers can build with it, and extend InfluxData's leadership into the next generation of time series infrastructure." Vaghani joins InfluxData from Tiyaro, an AI infrastructure software company he co-founded and led as CEO. He previously served as SVP and General Manager of AI and IoT at Nutanix, leading product, engineering, and go-to-market for its edge computing and IoT application platform. Before that, he co-founded and served as CTO of PernixData, a flash virtualization company acquired by Nutanix, and began his career at VMware as a Principal Engineer and storage CTO, spending a decade building core storage technology for vSphere. "Time series data sits behind many of the world's most demanding systems, and the expectations for the platforms that manage real-time data keep rising," said Satyam Vaghani, Chief Product Officer at InfluxData. "InfluxData has the technical leadership and product ambition to keep raising that bar. The opportunity now is to extend those strengths across the platform and help customers move faster as their systems grow more complex." About InfluxData InfluxData is the creator of InfluxDB, the leading time series database used by millions of developers building real-time systems. InfluxDB captures and analyzes massive streams of high-resolution data, giving AI models the context for predictive maintenance and anomaly detection so systems can detect, alert, and adapt as conditions change. Built for high performance at any scale and in any environment, InfluxDB delivers the speed and flexibility developers need to manage today's most demanding workloads. InfluxData is a remote-first company with a globally distributed team. Learn more at www.influxdata.com. Ready to get started? With 1B+ downloads and counting, developers choose InfluxDB as the leading time series database.

Associated Press
Jun 24th, 2026
InfluxData launches Telegraf Enterprise for centralized control of large-scale telemetry deployments

InfluxData has launched Telegraf Enterprise, offering centralised control for large-scale Telegraf deployments. The product features Telegraf Controller, a management console that provides fleet-wide visibility, automated configuration management, and enhanced security for operating telemetry pipelines across distributed environments. Telegraf, with over five billion downloads and 400+ plugins, is an open-source standard for connecting data sources across cloud, edge and physical infrastructure. The Enterprise version enables teams to manage tens of thousands of agents from a single control plane, standardising configurations and automating rollouts whilst reducing manual errors. Telegraf Controller is available today with a free tier. Telegraf Enterprise includes commercial support for the open-source agent and all 400+ official plugins.

InfluxData
Jun 17th, 2026
What's new in InfluxDB 3.10: performance beta expanded with new enterprise features.

What's new in InfluxDB 3.10: performance beta expanded with new enterprise features. In its last release, InfluxData, Inc. introduced a beta of performance updates designed for heavier, more complex time series workloads. InfluxDB 3.10 expands that beta to include enterprise features that give teams more control as they scale and manage larger workloads in InfluxDB 3. This release adds end-to-end backup and restore, row-level deletes, bulk import from Parquet, user management, and an RBAC preview to the previous performance beta. It also includes cross-database plugin queries, a new readiness endpoint, and compaction improvements for InfluxDB 3 Enterprise. Together, these updates help teams evaluate the next phase of InfluxDB 3 performance and scale with more of the operational tooling they need to manage real workloads. InfluxData, Inc. is inviting customers to test this next phase of InfluxDB 3 performance and scale, share feedback, and help shape the path to general availability. Expanded capabilities for the performance beta. The performance improvements InfluxData, Inc. previewed in InfluxDB 3.9 continue to mature in beta. These updates are designed for teams testing heavier time series workloads, including higher ingest, wider schemas, sparse data, and more demanding recent-data queries. The beta remains opt-in and is not yet the default, so existing deployments continue running unaffected unless teams explicitly enable it with the -use-pacha-tree flag. Once users opt in to the beta, InfluxDB 3.10 adds operational capabilities, so teams can do more than test raw performance. They can protect data, recover from known-good states, remove bad or unnecessary rows, and bring existing Parquet datasets into InfluxDB 3 for evaluation. That matters for teams working with real production patterns, where data rarely arrives perfectly clean and workloads rarely stay fixed. The following capabilities are available only when using the performance beta, enabled with the -use-pacha-tree flag: * End-to-end backup and restore: You can now run full backups that capture cluster state and compacted data for easy rollbacks. Restores run asynchronously, allowing you to recover data into a fresh store for disaster recovery or roll a live cluster back to an earlier point in time. InfluxData, Inc.'ll soon be adding incremental restores to give you even more control over your restore points. * Row-level deletes: Teams can now remove specific rows based on time ranges or tag predicates rather than dropping entire tables when data needs to be purged. The compactor applies these changes asynchronously in the background, allowing teams to clean up production data without interrupting operations. * Bulk import from Parquet: A new bulk-import function makes it easier to bring historical or external data into InfluxDB 3. Teams can point InfluxDB at a generic Parquet file or an entire directory, use simple column mappings, and ingest each file as an independent import job. User authentication and RBAC preview. As time series workloads become more central to production systems, access control becomes increasingly important. The same database may support operators monitoring live systems, developers building applications, analysts exploring historical data, and automated services writing or transforming telemetry. InfluxDB 3.10 Enterprise introduces a preview of multi-user authentication and role-based access control (RBAC). This feature is turned off by default for this release. When enabled, operators can configure traditional username and password logins that issue JWTs, or opt for external identity management through OAuth and OIDC. 3.10 also introduces built-in roles, including Admin, Auditor, and Member, to enforce proper boundaries across your teams. Best of all, your existing token workflows will continue to work exactly as they do today without any breaking changes. General updates and improvements. InfluxDB 3.10 also includes several capabilities that work across all deployments to streamline data pipelines and improve cluster management. Cross-Database plugin queries. Time series data often moves through stages: raw telemetry, cleaned data, downsampled rollups, forecasts, anomaly scores, and application-ready views. Those stages may live in different databases, but teams still need to connect them without building unnecessary external pipelines. In 3.10, Processing Engine plugins are no longer restricted to querying their own database. Now, a plugin can query any database residing on that node. This unlocks read-from-one, write-to-another data pipelines, such as reading raw telemetry from a staging database and writing compacted rollups or machine learning forecasts to a production database. Readiness endpoint. Production deployments need health checks that reflect whether a node can actually serve traffic, not just whether a process is running. InfluxDB 3.10 adds a new /ready endpoint. Instead of a basic uptime check, this endpoint verifies whether the node can successfully reach its underlying object store, giving operators a more reliable signal for traffic routing. Improved compaction. Under heavy ingest, compaction needs to keep pace with incoming writes so query nodes can access optimized data. When compaction stalls, the path from raw writes to efficient queries slows down. InfluxDB 3.10 introduces parallel compaction, ensuring that query nodes access fully compacted data more quickly and serve queries faster. Get started with InfluxDB 3.10. InfluxDB 3.10 is available now. To get started, download the latest version or pull the newest Docker image for Core or Enterprise. InfluxDB 3 Core remains free and open source under MIT and Apache 2 licenses, optimized for recent data and local workloads. InfluxDB 3 Enterprise adds long-range querying, clustering, advanced security, and full operational tooling for production deployments. Check out the docs (Core, Enterprise), try the release in your environment, and share your feedback in Discord or the Community Slack. InfluxData, Inc. want your feedback as the performance beta continues to mature. Ready to get started? With 1B+ downloads and counting, developers choose InfluxDB as the leading time series database.

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