- Видео 347
- Просмотров 278 367
Imply
США
Добавлен 4 мар 2018
Imply, founded by the original creators of Apache Druid®, develops an innovative database purpose-built for modern analytics applications. Imply is driving a new era in data analytics, called Analytics in Motion, where interactive queries, real-time and historical data at unlimited scale, combine with the best price/performance, to realize the full potential of data.
How Finix is Leaning Into Real-Time data with Apache Druid and Imply Polaris with Ross Morrow
On this episode, we are joined by Ross Morrow, a Software Engineer at Finix, the payment processor working to create the most accessible financial services ecosystem in history. Finix’s B2B payments platform is designed for flexibility and scalability, streamlining financial transactions for businesses and delivering a truly customer-centric experience. Faced with the need for a powerful database for real-time insights, Finix turned to Apache Druid. Listen to learn how they’re able to access real-time data with sub-second query times, how they transformed their data operations, and how Imply Polaris is helping them get all the benefits of Druid without the burden of maintenance or overhea...
Просмотров: 39
Видео
Securing the “Crown Jewels”: A Journey through Druid Database Security with Carrell Jackson
Просмотров 19Месяц назад
On this episode, we’re going all in on cybersecurity! Helping us with what critical aspects of security you need to focus on when building analytics applications is Carrell Jackson, CISO at Imply. We’ll discuss the importance of protecting sensitive data by implementing role-based access control and encryption and hear about best practices for securing a Druid cluster. Listen to learn more abou...
AWS IoT Core + Imply Polaris
Просмотров 432 месяца назад
Check out Rohan's vid below, and read about some#IoT use cases and customer stories featuring Rivian, Innowatts, PepsiCo, Thing-it, and more here: bit.ly/3JlBhlN
AWS IoT Core + Imply
Просмотров 1372 месяца назад
Rohan Joshi's quick demo walks through how AWS IoT Core works with Imply. Learn about why Imply is trusted by developers at leading organizations as their real-time database for IoT monitoring and analytics here: bit.ly/3U1ss6Q
Inside Apache Druid 29.0: Getting up to Speed on Druid’s Performance, Ecosystem, and SQL Complian...
Просмотров 533 месяца назад
On this episode, we explore Apache Druid 29.0, focusing on three specific themes: performance, ecosystem, and SQL compliance. Discover new features such as EARLIEST / LATEST support for numerical columns, system fields ingestion, and enhanced array support like UNNEST and JSON_QUERY_ARRAY. In addition, get the full scoop on community-contributed extensions like Spectator Histogram and DDsketch ...
Druid in 100 Seconds: EXPORT
Просмотров 593 месяца назад
On the ecosystem side, Druid 29.0 has improved the multi-stage query (MSQ) engine, adding more cloud support and the ability to export data. Though experimental right now, it enables better integration with data platforms where we want to take advantage of Druid’s data processing in downstream systems. Check out this “Druid in 100” video and let us know what other formats you’d like to see (it’...
Druid in 100 seconds: PIVOT/UNPIVOT
Просмотров 793 месяца назад
Imply's Senior Developer Evangelist, Reena Leone chats with Imply's Senior Developer Advocate, Sergio Ferragut about PIVOT/UNPIVOT in Apache Druid 29.0. ... In less than 100 seconds. Read the notebook here: bit.ly/3IotyTz
A Year in Review: Apache Druid's 2023 Highlights with Peter Marshall
Просмотров 263 месяца назад
In this special episode of Tales at Scale - this is our final episode of our first season! - Peter Marshall, Director of Developer Relations at Imply joins the show to discuss the highlights of 2023 for Apache Druid. We dive into the significant feature releases and enhancements that have transformed Druid over the past year, including the SQL standardizaion, query from deep storage, experiment...
Revenue at scale billing for millions of events a second
Просмотров 1396 месяцев назад
Revenue at scale billing for millions of events a second
Splunk's Journey to Imply Data Compaction At Scale
Просмотров 666 месяцев назад
Splunk's Journey to Imply Data Compaction At Scale
Streaming Ingestion: A Look Under The Hood
Просмотров 616 месяцев назад
Streaming Ingestion: A Look Under The Hood
Strivr: Using inline datasources with Druid queries
Просмотров 306 месяцев назад
Strivr: Using inline datasources with Druid queries
Wave Money Transaction Analytics Journey
Просмотров 196 месяцев назад
Wave Money Transaction Analytics Journey
SpectatorHistogram Efficient Percentile Approximations
Просмотров 306 месяцев назад
SpectatorHistogram Efficient Percentile Approximations
Load, Load, Don't Drop, Drop & then Kill
Просмотров 616 месяцев назад
Load, Load, Don't Drop, Drop & then Kill
Moving ingestion from 3 hours to 5 minutes - Challenges and Mitigations
Просмотров 836 месяцев назад
Moving ingestion from 3 hours to 5 minutes - Challenges and Mitigations
From Reaction to Action Atlassian’s Proactive Scaling Journey
Просмотров 206 месяцев назад
From Reaction to Action Atlassian’s Proactive Scaling Journey
Druid Operator Bridging Kubernetes and Apache Druid
Просмотров 1456 месяцев назад
Druid Operator Bridging Kubernetes and Apache Druid
Enhancing Druid's Analytics with Apache Arrow and Flight SQL 1
Просмотров 1106 месяцев назад
Enhancing Druid's Analytics with Apache Arrow and Flight SQL 1
Druid + Kubernetes Cheaper and More Responsive Auto Scaling Ingestion
Просмотров 916 месяцев назад
Druid Kubernetes Cheaper and More Responsive Auto Scaling Ingestion
A truly technical introduction to Apache Druid
Просмотров 7046 месяцев назад
A truly technical introduction to Apache Druid
Druid Summit 2023 Keynote: When I Decide To Use Druid Instead Of A Data Warehouse
Просмотров 856 месяцев назад
Druid Summit 2023 Keynote: When I Decide To Use Druid Instead Of A Data Warehouse
Druid Summit 2023 Keynote: Druid 28 and beyond
Просмотров 1096 месяцев назад
Druid Summit 2023 Keynote: Druid 28 and beyond
Druid Summit 2023 Keynote: Real-Time Analytics in the Real World
Просмотров 1756 месяцев назад
Druid Summit 2023 Keynote: Real-Time Analytics in the Real World
dude you are a legend. not many people make tutorial like this
Audio quality :(
Hi Peter, it was a grand meetup yesterday... about Apache Druid, FlightRadar24 and more. Gratitude for the engaging talk. It was an awesome tech learning session!! 🙂👍
AMAZING - AN EXPLAINATION
'Promosm' 😴
Great tutorials. It shows the real power of Druid.
Debbugging is so tough for Druid. I wish Imply team puts a video for troubleshooting Druid !
Crystal clear. Only a person with that extreme reverse writing technique can provide that good explanation. Thanks!
Thanks for sharing this, I think a quick screen share with example(s) would be a great add.
well explained
Is druid ingest avro format data from kafka?
How we can ingest avro data from kafka?
Great presentation! Thank you :)
thank you for the great presentation. it was a full of 22 minutes.
Here's a summary, as created by Google Bard: This video is about stream analytics and how it is different from traditional data warehousing and stream processing. The speaker, Darren, starts by defining what stream analytics is and why it is important. He then discusses the limitations of data warehouses and stream processors for real-time analytics. Finally, he introduces Apache Druid as a real-time database that can be used for stream analytics. Here are some key points from the video: Stream analytics is the process of analyzing data as it is being generated. Traditional data warehouses are not designed for real-time analytics because they require data to be loaded in batches. Stream processors can be used for real-time analytics, but they are limited in their ability to handle large amounts of data and complex queries. Apache Druid is a real-time database that can be used for stream analytics. It is designed to ingest data in real-time and to make it queryable immediately. Apache Druid can also be used to store historical data, which allows you to compare real-time data to historical data. If you are interested in learning more about stream analytics, I recommend watching this video. It is a great introduction to the topic and provides a lot of valuable information.
too quiet comparing to other vides ;-(
love it!
Can apache druid take streaming data from apache pulsar topic?
Great presentation!
Great presentation
Excellent!
Amazing
excellent job in explaining - thank you!
Incorrect scaling of dimension axis! Is the data reliable?
Awesome.. Conceptually clear..✨ Thank you!
Can I run druid on windows? Can it be used as a big data warehouse and to be used with python?
Windows is garbage and you should be ashamed for using it. However there is a Python library, and a RESTful API.. so yes on that.
@@roharbaconmoo 🤣
😂
Python is garbage and you should be ashamed for using it. However, since there's an API, you should use a real language to build a library.
perfect!
thanks
Hello Glen, let's talk I can finish working on the Jira Service Desk. My role at Facebook was closed due to budget.
Nice explanation. What kind of board is that?
Amazing presentation. Can you please share druid query benchmark tool?
Thanks for making druid tutorial hands-on oriented with the 0.21 version. Now(feb2023) that i am in the 25.0.0 version how can i perform these hands-on .
Not sure how you claimed snowflake connection with Storage to Compute is slow.
can u provide ur blog link here
You are the best!
How did you do the disappearing drawings?
I drew the whole diagram on an iPad using GoodNotes, created versions of each diagram, where I erased portions, organized them in a notebook so they would build in order. The recording ended up with the page flips from GoodNotes, so I split the audio and video and then used transitions in Camtasia to simulate drawing out the next portion. 🙂
@@sergioferragut7439 omg :)
I'm considering using druid and these lectures are highly valuable please post more deep dives. Also real life use cases with end to end design and implementation and how to unit test ingestion spec would be highly valuable.
How about memory requirements comparison?
thinking back to a bunch of greps and tails, this must be valuable. thanks!
This comparison is, of course, biased, so take it with a grain of salt.
19:43 comparison
Thanks a lot😀
"Druid, it's like a search system, and a data warehouse, and a time series database all mixed together"
Hi Please help me. i want to create connection between Apache druid and Power bi. How can send data in power bi from druid.
ruclips.net/video/GvVYG6chYoI/видео.html, Apache Pinot vs Apache Druid & Real-Time Analytics (LinkedIn Profile Insights)
𝔭𝔯𝔬𝔪𝔬𝔰𝔪
Thanks Darin! very useful :-)
Great explanation! Thanks Carl !
Lol, you guys suck - filtering comments that mention alternative databases.
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