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Splunk Federated Search lets you reach into S3. Lumi Loglake makes S3 feel like it’s already in Splunk.
Read the new blog here: bit.ly/4etNuoP
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Teams are increasingly moving log data into AWS S3 to reduce costs and extend retention. Both Lumi Loglake and Splunk Federated Search to S3 help you query data in AWS S3 to lower costs, however the two technologies have several notable differences.
bit.ly/4etNuoP
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Imply Lumi Loglake vs Splunk Federated Search for S3:
Get the side-by-side comparison here 👇
bit.ly/4etNuoP
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Query unstructured logs directly where they already live.
Lumi Loglake launches next month at @Databricks #DataAISummit.
Get a first look here: bit.ly/3RCFN6N
Imply retweeted
Get a first look at Lumi Loglake here (bit.ly/3RCFN6N) and see it live in action at @Databricks #DataAISummit in June!
Imply retweeted
Lumi Loglake, launching this month at Databricks #DataAISummit.
Get a first look here: bit.ly/3RCFN6N
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THIS MONTH!
We're less than 2 weeks out from @Databricks #DataAISummit! Catch Gian's session, “From Splunk to Databricks: Unlocking Open, Scalable Observability in the Lakehouse” on June 17 at 1:10PM in Theater 5.
bit.ly/3PEUzJH
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“With an Observability Warehouse as the scalable data layer, teams keep telemetry data accessible at scale without increasing costs.”
- Eric Tschetter, Chief Architect, Imply
bit.ly/3QcmtN4
@InfoWorld @nyike
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TECHZINE GLOBAL
Observability warehouses, the next structural evolution for telemetry techzine.eu/blogs/data-manag… via @techzine @implydata @techzine
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80% of teams offload logs just to stay on budget, but #AI is pushing telemetry to a breaking point.
In 2026, the "#Observability Warehouse" will fix the black box. Learn why the future is decoupled.
Read @ImplyData's Eric Tschetter #predictions: vmblog.com/archive/2025/12/1…
Imply retweeted
Here’s @ImplyData showcasing their new stuff in the field of Observability. 👀
Imply retweeted
ICYMI: Imply Lumi is out now.
Learn about the industry's first Observability Warehouse here: bit.ly/3JLjlET
Imply retweeted
One week ago, at @Splunk #conf25, we launched the industry's first Observability Warehouse, Imply Lumi.
So... what's an Observability Warehouse?
(and what does it matter?)
Imply's Senior Product Marketer, Matt Morrissey explains. (Read more here: bit.ly/3JLjlET)
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📢 Meet Imply Lumi, the industry’s first Observability Warehouse.
Imply Lumi helps teams keep more data, search it faster, and spend less — without replacing their existing tools. bit.ly/3JLjlET
Imply retweeted
Replying to @implydata
@implydata Unveils Lumi: The First Observability Warehouse
itdigest.com/cloud-computing…
#analytics #datascience #Imply #ImplyLumi #ITDigest #news #observabilitytools #ObservabilityWarehouse
Imply retweeted
Building scalable fraud detection starts with rethinking your data architecture.
Join Braeden Quirante from Confluent, Benjamin Hopp from @implydata, and Weifan Liang from @awscloud learn how leading companies are detecting anomalies faster and powering fraud models with data streaming.
Register now for the webinar on May 29 → cnfl.io/4jWqXRX
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Tick Tock Tick Tock! ⏰ Just ONE WEEK until #Current25 lands in London! 🎉 Calling all Developers, Execs, Engineers, and Architects this is the event for you! Don't miss your chance to connect with the data streaming and Kafka communities, hear from industry leaders, and explore the future of real-time data and AI. 👍 YOU don't want to miss this - Last chance to register: cnfl.io/4gQbDnJ
Imply retweeted
👏
Druid is different! 💥
This October, channel your inner data practitioners. ✨
Join us for the Huddles Apache Druid 2.0 meetup by @OCD_India , aiming to bring a breakthrough in the data world.🙌🏻
Master the craft of querying this October, the month of data engineering.
Imply retweeted
The Imply Developer Center walks readers through common scenarios, explaining key features, highlighting helpful shortcuts and solutions, and more.
🍂 Here's our Fall round up of the best of our Dev Center articles, tutorials, recipes, and lessons: bit.ly/3TQrfPv
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October 17, Zurich, Switzerland:
Streaming Analytics Stack: @apachekafka & @Implydata / @druidio for Time-series data at @Swisscom, with Imply's @Hellmar_Becker: bit.ly/4gGC00n
















