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Prikvačeni tweet
We think this is a big step in making stream processing easier. I'm really excited about it.https://www.confluent.io/blog/intro-to-ksqldb-sql-database-streaming …
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Jay Kreps proslijedio/la je Tweet
This is a wonderful 4-part series by @miguono. The whole thing pivots around the relationship between the stream and the table but it's really a comprehensive guide to understanding the nature of data in flight.http://tiny.cc/fr0tiz
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A really good primer by
@miguno on the fundamentals of events vs state, streams vs tables, and@apachekafka and stream processing.https://www.confluent.io/blog/kafka-streams-tables-part-1-event-streaming/ …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Neha has done so much to help build both Apache Kafka and
@confluentinc . From the early Kafka development at LinkedIn, to helping found and grow Confluent to where it is today, we wouldn't be where we are without her.https://twitter.com/nehanarkhede/status/1216767676598517762 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jay Kreps proslijedio/la je Tweet
A good tutorial by
@rmoff with code examples on how to implement a real-time app with@ksqlDB,@Elastic, and@neo4j.https://rmoff.net/2019/12/18/detecting-and-analysing-ssh-attacks-with-ksqldb/ …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jay Kreps proslijedio/la je Tweet
“Stream processing” is a term that you might hear a lot, but what exactly does it mean? How would you explain it to a newcomer? And what are its key properties? Time for a quick lesson. 1/pic.twitter.com/j4rRwX9pFU
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Event streams and drug discovery. Very cool.https://twitter.com/confluentinc/status/1205155872088952833 …
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Jay Kreps proslijedio/la je Tweet
Gwen Shapira on the Power of Event-Driven Architecture http://bit.ly/2E8qIkt
@jkriggins@gwenshap@CloudBees#sponsoredHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jay Kreps proslijedio/la je Tweet
Thanks to our employees


, Confluent made @Comparably's annual Best Company Culture list! https://www.comparably.com/blog/best-company-culture-2019 …@businessinsider article: https://www.businessinsider.com/comparably-the-best-places-to-work-in-2019#25-northside-hospital-1 …pic.twitter.com/Sl1zbr4QGA
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Jay Kreps proslijedio/la je Tweet
My
@InfoQ talk
on the "Future of Data Engineering" is up! I cover the six stages of data pipeline maturity:
0. None
1. Batch
2. Realtime
3. Integration
4. Automation
5. Decentralization
Check it out!
(I'm so sorry for the link picture)https://www.infoq.com/presentations/data-engineering-pipelines-warehouses/ …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Nice
@ksqldb edition of@charllamprecht’s famous blog tutorials on@apachekafka, stream processing, and...doughnuts. :-)https://twitter.com/charllamprecht/status/1199034334864445441 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jay Kreps proslijedio/la je Tweet
So happy to finally take all the wraps off what my team has been working on at
@confluentinc.@ksqlDB is the start of a really powerful idea to make a substantial dent in the complexity of building stream processing applications. 1/https://twitter.com/ksqldb/status/1197183854332669953 …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
This is still early days for this line of work, but we think this is a really promising direction for making stream processing easy and ubiquitous. Check it out, the blog has the full story.
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You can control connectors directly from within SQL, and can do real-time lookups against the tables you are materializing in your stream processing queries.
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This release of KSQL let's you simplify this significantly by bringing together these different capabilities.pic.twitter.com/J0cFL74iwb
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It's enough to make you long for the good old days of CRUD applications, where at least you had just one database that served the basic needs of the app.
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The stack is usually something like Kafka, a stream processing layer, a traditional database, various connectors, etc.pic.twitter.com/OHX5CexYlX
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The reality is that event streams are becoming ubiquitous in software engineering but the stack supporting stream processing is still a bit too complex. You end up with lots of moving parts and it's up to you to integrate them all.
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Jay Kreps proslijedio/la je Tweet
We’re making a big change to Sentry today:https://blog.sentry.io/2019/11/06/relicensing-sentry/ …
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Jay Kreps proslijedio/la je Tweet
Welcome aboard the rocket ship, Erica Schultz! We’re honored you’re joining the team as our President of Field Operations. https://www.confluent.io/press-release/erica-schultz-president-field-operations/ …pic.twitter.com/2PnxZOJi23
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