influxDB & ju:niz Energy Storage - Technical case study

Technical case study of ju:niz successfully transforming their architecture using InfluxDB presented at Linux Foundation Energy Summit 2024

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ju:niz Energy Storage:
Case Study
Suyash Joshi
sjoshi@influxdata.com
Sr. Developer Advocate
InfluxData

@suyashcjoshi
#LFEnergySummit

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Who is ju:niz?

●Pioneer of the decentralised energy
transition, based in Germany

●Focuses on Large-Scale Storage

●Energy Supplier to Residential Districts

●Intelligent Energy Management System

Website: https://juniz.com/en

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ju:niz’s Business & Technical Challenges
Data Demands: Need for real-time and historical data for decentralized energy management
System Limitations: Legacy systems couldn't handle growing data volumes
Sync Issues: Unreliable syncing caused data loss between edge and central systems
Storage Constraints: Limited storage led to restrictive data retention policies
Re-architecture of the old System Infrastructure was much needed!
Lack of real time deep insights of plant batteries, sensors and other modules that were
critical for business - trading decisions, battery maintenance etc.

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InfluxDB & ju:niz

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Time Series Data
Warehouse IoT
Devices
Ingest - A high amount of data streaming in at nano
second precision

Compression - The ability to store this large data set
without breaking the bank

Cardinality - The need to store wide rows,
timestamped data with multiple values

Querying on Time - Instead of indexes or values,
querying on time
Track + Monitor
application
infrastructure
Metrics from
everywhere
Robotics and
Green Energy

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TIME SERIES
Rise of time series data
DOCUMENT SEARCHRELATIONAL
•Events, metrics, time-stamped
•For IoT, analytics, cloud native
•Distributed
search
•Logs
•Geo
•High
throughput
•Large
document
•Orders
•Customers
•Records
Time series is fastest growing
data category by far
All others
Time series
source: DB Engines
influxdb

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Uniquely equipped for time series data
Scale
Designed to scale for large volumes of time series data
Distributed
Non-blocking high volume writes and reads
Availability
Write and read availability are prioritized over consistency
Management
Data lifecycle management with built-in data retention
Flexible
Schema on write

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InfluxDB 3.0: A Peek inside FDAP Stack
Flight for high performance
network data transfer
DataFusion for optimized query
planning and execution
Arrow for in-memory columnar
analytics
Parquet for best-in-class
compression and storage
F
D
A
P
●Increased developer productivity

●Rich Integrations & Seamless Interoperability

●Open Standards based, always improving

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Edge Data Replication (EDR)
EDGE
EDR removes a lot of complexity
around setting up, and maintaining
Edge to Cloud replication and thus
enabling Customers to bring OT and
IT closer and eliminate data silos.
HUB

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Industrial IoT (IIoT) Partnerships & Integrations

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InfluxDB for ju:niz energy
12
PLC

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ju:niz Architecture (Before)
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(OSS)
v1
Limitation:
-
-PLC Controller: Need to
send 50K data points
(infeasible, unreliable)

-Battery Information :
Over 80k data points
(infeasible)

-Architecture lacked data
replication


PLC
Controller(s)

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ju:niz Architecture (After)
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Thousands of data points written every 5 seconds
(OSS)
querying every device
in the plant
(a lot more data points)
PLC
Controller(s)

Other Devices
(batteries, inverters etc)
10X better compression with much
larger data storage capacity
Queries data
(v3)

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Demo Video by ju:niz
15

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InfluxDB for ju:niz : Recap
●Smooth Integration: Seamlessly integrated InfluxDB OSS (v1) with InfluxDB Cloud Dedicated (v3) with
telegraf, simplifying large volumes of data collection from plant servers and devices.

●Legacy Challenges: Overcame incompatibilities with older hardware that caused data transmission
issues in InfluxDB OSS.

●High Availability & Reliability: Enhanced uptime with edge data replication and reliable data sync.

●Stable Performance: Achieved smooth data ingest, enabling real-time monitoring and analytics of the
plant environment.

●Scalable Solution: InfluxDB Cloud Dedicated provided a fully-managed, single-tenant solution for large
and inconsistent workloads.

●Cost-Effective Storage: Leveraged low-cost storage options with increased capacity.

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Resources
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Resources

●ju:niz case study: https://www.influxdata.com/customer/juniz
●Blogs : https://www.influxdata.com/blog
●Documentation: https://docs.influxdata.com
●InfluxDB University (free training): https://influxdbu.com
●Hybrid Architecture Course: https://killercoda.com/influxdata/course/Training/influxdb-hybrid-iiot
●Community: https://influxcommunity.slack.com & https://community.influxdata.com

❖www.influxdata.com/cloud
❖via cloud marketplace

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Any questions ?
19
Suyash Joshi
sjoshi@influxdata.com
Sr. Developer Advocate
Ricardo Kissinger
[email protected]
Head of IT Infrastructure & IT Security

20. | © Copyright 2024, InfluxData20
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