Apurva Mehta
@apurvamehta.com
Co-Founder and CEO of @responsive.dev. I write about stream processing and company building. Views are my own. 🌐 apurvamehta.com
The inner join between sets of people who build databases, write, and draw? Low cardinality. I'm in that set, so I'm starting a blog! Here's my first post: www.bitsxpages.com/p/frameworks...
frameworks for understanding databases
building mental models for tradeoffs in performance, availability and durability in data systems
bitsxpages.com
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
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 · last yr.Interesting. www.kafkastreams.money
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
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
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
I’m excited to listen to this one. Some of my favorite folks all in one podcast 😀
Tech on the Rocks@totrrocks.bsky.social · last yr.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. 🎧 👉
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.
responsive.dev
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
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
responsive.dev
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
responsive.dev
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
(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.
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
Should you use Kafka? If so, when? And what are the tradeoffs presented by the dizzying variety of Kafka-adjacent technologies? I hope that my latest blog post provides unique and useful answers to these questions. Let me know what you all think! 👉 www.responsive.dev/blog/why-whe...
Thanks everyone for all the feedback on blog post ideas! Performance and upgrades were most popular so stay tuned for these deep dives - for beginners and advanced users alike Check out our new Kafka Streams 101 site and subscribe to get notified for these and other upcoming lessons! bit.ly/40LWJZL
Kafka Streams 101 | Responsive
Learn to build bulletproof Kafka Streams applications
bit.ly
This will be the foundation for being able to branch @kafkastreams.bsky.social apps to support seamless blue/green deploys. It also allows you to branch a previous version of the state to debug an issue from the past. Powerful stuff coming to the world of stream processing!
Chris@chris.blue · 2y agoSlateDB now has clones 🤯 Users can clone an existing DB's data to a new location. It's nearly instantaneous since it references the data from the old bucket rather than copying. Writes to the clone update the new location. Compaction lazily merges old data into the new directory./ht @responsive.dev
I'm enjoying putting the finishing touches on my next blog post on the Why, When, and How of Kafka applications. It's a distillation of my point of view from a decade in the space and I hope it's as useful to read as it was fun to write. Coming Tuesday!
I've used ChatGPT and/or Gemini to brainstorm ideas for presenting concepts visually multiple times recently. They have unlocked ideas I wouldn't have thought of otherwise. And sometimes, they generate the graphics. For the rest, Figma is perfect. It's such a major boost either way!
How did Responsive simplify its architecture and achieve monstrously high availability with unlimited scale potential? Co-founder @almog.ai will share how replacing RocksDB with #ScyllaDB in #Kafka Streams led to big wins for their team at Monster Scale Summit. www.scylladb.com/monster-scal...
The first of our Kafka Streams 101 Series. Practical knowledge on thinking about windowing and time in @kafkastreams.bsky.social We are going to ship new tutorials regularly over the next few months, and you can find them all here: www.responsive.dev/resources/ka...
Almog@almog.xyz · 2y agoKafka Streams 101: Windows & Time! 🕰️ What's the difference between event, stream and wall clock time? 🪟 What are the four different types of windows? ⁉️ What are the important error messages and metrics, and what do they mean? 👉 Read the full lesson here: www.responsive.dev/blog/windows...
There are some learnings that only come from having seen a wildly successful technology go from a nascent project to ubiquitous. These insights can change the trajectory for new tech. Jason's summary about error handling is a great read for practical engineers: github.com/slatedb/slat...
API Error Guidance · Issue #454 · slatedb/slatedb
Dumping a few thoughts on API errors. At the moment, we have a single flat error SlateDBError which is exposed through the public API. This is the same pattern used in Kafka and there are some less...
github.com
Sophie arguably has the best @kafkastreams.bsky.social blog posts on the internet. Now you get a say on what she should write about next!
Sophie Blee-Goldman@ableegoldman.bsky.social · 2y ago[1/5] Hey fellow Kafka Streams otters! You may have already seen my previous blog posts such as the "Debugging Rebalances" and "EOS guide" from last year (and if you haven't, go check them out! Links in thread) But now it's 2025, and time for me to think about what to write next...
Kafka Streams had an amazing 2024! Check out @ableegoldman.bsky.social's year in review, where she recaps the 25 major improvements the community made to Kafka Streams! www.responsive.dev/blog/kafka-s...
Kafka Streams Wrapped: 2024 in review
Kafka Streams had some tremendous additions and improvements in 2024. Here are the highlights.
responsive.dev
SlateDB now has range scans! An important feature for joins, time series, secondary indexes, and so on. Props to the folks @responsive.dev for getting this done. github.com/slatedb/slat...
It was so much fun to observe the @responsive.dev team brainstorm distributed state snapshots for Kafka Streams using SlateDB/RS3. Nothing beats the thrill of having a team of the best engineers solving hard problems with nothing but a whiteboard in front of them!
Great to see so many people online. If you want to hear about how Metronome scaled their Kafka streams apps to 10's of TBs of state and 10's of thousands of events/s, do tune in for the last few minutes!
Almog@almog.xyz · 2y agoStarting in 10 minutes! If you are in production with Kafka Streams or curious about how Metronome handles insane throughput in realtime, you won't want to miss this at 9:30AM PT. www.linkedin.com/events/q-a-s...
The momentum on SlateDB development can't be stopped! We're getting close to closing out another foundational RFC by @flaneur2024.bsky.social: transactions 🏦 Mostly taking inspiration from Badger, but there's some innovative stuff there. Check it out: github.com/slatedb/slat...
docs: Add rfc about Transaction by flaneur2020 · Pull Request #260 · slatedb/slatedb
fixes #248 this doc is still in WIP, but the discussion is open here. TLDR of this doc: Snapshot (with sequence number in keys) and WriteBatch are MUST before working on the Transaction feature SS...
github.com
