The document discusses the importance of time series data and the capabilities of InfluxDB, a time series database designed to collect, store, process, and manage time-stamped data. It highlights the evolution of technology over the last 10-20 years that enables enhanced data analysis, including advances in wireless connectivity, affordable sensors, and edge computing. Furthermore, it outlines the core functionalities of InfluxDB, including data collection, transformation, querying, and security management.

1. Paul Dix
Founder & CTO
paul@influxdata.com
@pauldix
Why Time Series &
InfluxDB

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If you want to observe
anything, you’re
collecting time stamped
data

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If you want to analyze and
learn from that data,
you’re working with time
series

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All data is based in time

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Everything that can be
instrumented will be
instrumented.

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Everything that can be
optimized will be
optimized.

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A few interesting use cases…

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Many others in vertical
farming, improved
water use, and energy

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What changed over the
last 10-20 years?

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Wireless speeds and
coverage

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Cheap sensors

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Compute power at the
edge

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Enabling hardware and
network requires
enabling software.

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Time series are historical
observations and
predictions of the future.

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Two kinds of time series

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InfluxDB will be the
home for time series
data of all kinds.

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Four common areas of functionality
• Collect & Transform
• Store & Query
• Process, Monitor, Alert, and Act
• Manage & Secure

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Three user experiences
• CLI, API, client libraries
• UI
• VS Code

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Functional Areas

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Collect
Transform, monitor at the edge

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Serialization
Format
Transform
Messaging
System
InfluxDB
Telegraf

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Serialization
Format
Transform
Messaging
System
InfluxDB
Telegraf

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Serialization
Format
Transform
Messaging
System
InfluxDB

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Serialization
Format
Transform
Messaging
System
InfluxDB
JSON
Protobuf
CSV
Line Protocol
Parquet
TSM

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Serialization
Format
Transform
Messaging
System
InfluxDB
JSON
Protobuf
CSV
Line Protocol
Parquet
TSM
MQTT
Kafka
Kinesis
Azure Event Hubs
GCP Pub/Sub

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Serialization
Format
Transform
Messaging
System
InfluxDB
JSON
Protobuf
CSV
Line Protocol
Parquet
TSM
MQTT
Kafka
Kinesis
Azure Event Hubs
GCP Pub/Sub
Flux
Python
Javascript/Typescript

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Store
Distributed, federated, query

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Query
• Flux
• InfluxQL
• SQL (next year)

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InfluxDB IOx
• MIT & Apache 2 License
• New core in Rust
• Apache Arrow
• Apache Arrow Datafusion
• Apache Parquet
• Unlimited cardinality
• Object storage durability
• Bulk import/export
• Embedded Javascript/Typescript

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IOx Router
Kafka
IOx Query Server IOx Query Server
IOx Router IOx Router
Object Storage
InfluxDB IOx Cloud Architecture

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InfluxDB Cloud
InfluxDB InfluxDB InfluxDB InfluxDB InfluxDB

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Process
Monitor, alert, act

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Serialization
Format
Transform
Messaging
System
InfluxDB
Process, monitor,
alert, act

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Serialization
Format
Transform
Messaging
System
InfluxDB
Process, monitor,
alert, act
Flux
Python
Javascript/Typescript

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InfluxDB Cloud
InfluxDB InfluxDB InfluxDB InfluxDB InfluxDB
Push processing
to the edge!

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There is overlap in
collect, store, and
process!

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Manage
Secure, audit, inspect

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Manage
• Security policies
• Usage policies
• Deployment of Tasks
• Audit logging
• Schema locking & enforcement

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Developer experience

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GitOps flows

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Next Year
• InfluxDB IOx
• SQL support
• Unlimited Cardinality
• Ingest from messaging systems
• MQTT
• InfluxDB at the edge
• Tasks in Python & Javascript
• Bulk import/export
• Developer tooling

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Thank You
paul@influxdata.com
@pauldix