Author | Lightnews

Apurva Mehta @apurvamehta.com · Sep 10

Correct. The new site is a temporary one, more details will follow as we firm up our new plans.

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Apurva Mehta @apurvamehta.com · May 6

wow. that's surprising!

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Reposted by Apurva Mehta

Chris @chris.blue · Apr 22

Today marks SlateDB’s one year anniversary! It’s been a lot of fun. Thanks to @rohanpd.bsky.social @flaneur2024.bsky.social @almog.ai @vigneshc.bsky.social @paulbutler.org Jason Gustafson, David Moravek, and many others for joining the project. 😀

SlateDB - An embedded storage engine built on object storage | SlateDB

Description will go into a meta tag in <head />

SlateDB.io

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Apurva Mehta @apurvamehta.com · Apr 16

That looks super interesting. There seems to be a burst of innovation in this space of better developer abstractions on top of data systems recently.

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Reposted by Apurva Mehta

Chris @chris.blue · Mar 31

I’m a sucker for a good cost calculator. This one is pretty slick. Lots of components contribute to cost in Kafka Streams.

The Streaming Otter @thestreamingotter.bsky.social · Mar 29

Interesting.

www.kafkastreams.money

Kafka Streams Cost Calculator | Estimate Your Kafka Streams Application Costs

Free tool to analyze and estimate the costs of running Kafka Streams applications. Calculate compute, storage, and operational costs for your Kafka Streams deployment.

www.kafkastreams.money

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Apurva Mehta @apurvamehta.com · Mar 22

Looking forward to it!

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Reposted by Apurva Mehta

Chris @chris.blue · Mar 17

SlateDB 0.5.0 is out!

Features:
- Checkpoints
- Clones
- Read only client
- Split/merge database foundation
- TTL filtering on reads
- Last version with breaking byte format changes

By the numbers:
- 62 commits
- 2 new contributors
- 10 total contributors

github.com/slatedb/slat...

Release v0.5.0 · slatedb/slatedb

What's Changed Refactor Block Tests to Use Table-Driven Test Cases by @samsond in #410 Update await calls in README.md by @criccomini in #425 chore: Apply table driven test for sst.rs by @jeffreyl...

github.com

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Reposted by Apurva Mehta

Luke Hedger @lukehedger.dev · Mar 16

Related: super interesting discussion on stateful stream processing vs OLTP with @apurvamehta.com from @responsive.dev open.spotify.com/episode/1hsH... (start at 18:46)

Reinventing Stream Processing: From LinkedIn to Responsive with Apurva Mehta

Tech on the Rocks · Episode

open.spotify.com

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Reposted by Apurva Mehta

Kostas Pardalis @cpard.bsky.social · Mar 14

I'm always excited to chat with @apurvamehta.com about what @responsive.dev is building.

Streaming and real time as terms are being constantly reinvented as the market needs change rapidly, and Apurva is one of the best to talk about that.

Check the conversation here: techontherocks.show/15

Tech on the Rocks | Reinventing Stream Processing: From LinkedIn to Responsive with Apurva Mehta

SummaryIn this episode, Apurva Mehta, co-founder and CEO of Responsive, recounts his extensive journey in stream processing—from his early work at LinkedIn and Confluent to his current venture at R...

techontherocks.show

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Apurva Mehta @apurvamehta.com · Mar 7

If, on the other hand, IDEs can build proprietary adjacent tooling that integrates into developer workflows, they may become the integration point, and consequently an aggregator.

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Apurva Mehta @apurvamehta.com · Mar 7

Not sure what you mean by aggregator, but for me it's something that has a 2-sided network effect. I don't know if that applies to the IDEs: If 2 IDEs use the same foundation model, what's the structural barrier for one to copy the other over the medium term?

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Reposted by Apurva Mehta

Chris @chris.blue · Mar 6

I’m excited to listen to this one. Some of my favorite folks all in one podcast 😀

Tech on the Rocks @totrrocks.bsky.social · Mar 6

New episode: Reinventing Stream Processing with @apurvamehta.com from @responsive.dev

We cover:

Real-time vs low latency in streaming
Why stateful streaming is hard at scale
RocksDB, Postgres limitations
SQL vs flexible APIs
Decoupling state & compute with SlateDB.

🎧 👉

Tech on the Rocks

Join Kostas and Nitay as they speak with amazingly smart people who are building the next generation of technology, from hardware to cloud compute. Tech on the Rocks is for people who are curious…

techontherocks.show

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Apurva Mehta @apurvamehta.com · Mar 6

This week, our 101 series has @ableegoldman.bsky.social diving deep into the world of performance optimization for Kafka Streams.

This isn't just theory: she shows how we realized 10x throughput improvements by implementing these techniques in prod!

www.responsive.dev/blog/perform...

Kafka Streams 101: Optimizing your apps for maximum performance

Learn the concepts, configs, and application design strategies to get your Kafka Streams apps running as optimally as possible.

www.responsive.dev

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Reposted by Apurva Mehta

Tech on the Rocks @totrrocks.bsky.social · Mar 6

New episode: Reinventing Stream Processing with @apurvamehta.com from @responsive.dev

We cover:

Real-time vs low latency in streaming
Why stateful streaming is hard at scale
RocksDB, Postgres limitations
SQL vs flexible APIs
Decoupling state & compute with SlateDB.

🎧 👉

Tech on the Rocks

Join Kostas and Nitay as they speak with amazingly smart people who are building the next generation of technology, from hardware to cloud compute. Tech on the Rocks is for people who are curious…

techontherocks.show

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Reposted by Apurva Mehta

Sophie Blee-Goldman @ableegoldman.bsky.social · Feb 26

Next entry in the Kafka Streams 101 series: application lifecycle.

Very beginner friendly, but even the pros might find a useful tip or two -- for example: have you heard of the new standby task listener?

Check it out: www.responsive.dev/blog/app-lif...

Kafka Streams 101: Application Lifecycle

Learn how to properly start, stop, and manage the lifecycle of Kafka Streams

www.responsive.dev

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Reposted by Apurva Mehta

Sophie Blee-Goldman @ableegoldman.bsky.social · Feb 18

We're keeping the ball rolling on the Kafka Streams 101 series with yet another blog post! This time the focus is on configuration, and breaking down the most important configs to focus on for various needs (such as correctness, resiliency, etc)

Check it out here: www.responsive.dev/blog/importa...

Kafka Streams 101: The Most Important Configs

Learn which configurations are most critical for a reliable and efficient deployment

www.responsive.dev

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Reposted by Apurva Mehta

Responsive @responsive.dev · Feb 14

We are happy to announce that we have completed another SOC2 Type 2 audit along with completing another successful penetration test against our cloud services.

You can find the latest reports on our trust center: trust.responsive.dev

Responsive Trust Center

Responsive is a stream processing solution that brings disaggregated state, autoscaling, observability and enterprise-grade support to Kafka Streams. Eliminate unpredictable lag and rebalance instabil...

trust.responsive.dev

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Apurva Mehta @apurvamehta.com · Feb 13

wow. that's so cool. I never thought to use ChatGPT like that. It makes so much sense!

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Apurva Mehta @apurvamehta.com · Feb 13

What’s a query example that ChatGPT helped with?

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Apurva Mehta @apurvamehta.com · Feb 13

Most banks export your credit card transactions as CSV, with categorizations. I just load that into sheets and then make a chart out of it. Since most of the spending is on CC, it works pretty well.

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Apurva Mehta @apurvamehta.com · Feb 13

(3/3) Application upgrades were by far the #1 requested topic when we asked what the community would like to learn about earlier this year.

We hope you find this latest post in our Kafka Streams 101 series helpful!

www.responsive.dev/blog/topolog...

Kafka Streams 101: Topology Upgrades

A Kafka Streams 101 lesson to learn how to identify unsafe changes to a topology and the techniques to mitigate them

www.responsive.dev

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Apurva Mehta @apurvamehta.com · Feb 13

(2/3) @ableegoldman.bsky.social has been helping the @kafkastreams.bsky.social community with application upgrades since what feels like the beginning of time. She has now put all of that practical knowledge in one blog post to help everyone reason about their upgrades and do them correctly.

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Apurva Mehta @apurvamehta.com · Feb 13

(1/3) One of the hardest problems in the world of stream processing is upgrading stateful applications. Why? Because the events never stop, and your application has to handle the events correctly before and after a upgrade and if rewind your position in a topic.

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Reposted by Apurva Mehta

Chris @chris.blue · Feb 13

Had two people ask me for guidance about open source foundations this week. Lots of trepidation around Apache, not much familiarity with CNCF, and curiousity about why I chose Commonhaus for SlateDB.

Here are my thoughts:

Comparing Apache, CNCF, and Commonhaus | cnr.sh

I've used open source projects for over 30 years and contributed for about 20 of those. My first interaction with an open source foundation was with Apache when I began working with Apache Hadoop ...

cnr.sh

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Apurva Mehta @apurvamehta.com · Feb 12

We mostly use those two terms interchangeably. However, a remote storage solution could also have a disaggregated storage architecture with multiple layers: in-memory, on disk, object store, etc.

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