<!DOCTYPE html><html lang="en"><head><meta http-equiv="Content-Type" content="text/html charset=UTF-8"><meta charset="UTF-8"><meta name="viewport" content="width=device-width"><meta name="x-apple-disable-message-reformatting"><title>TLDR Data</title><meta name="color-scheme" content="light dark"><meta name="supported-color-schemes" content="light dark"><style type="text/css">
:root {
color-scheme: light dark; supported-color-schemes: light dark;
}
*,
*:after,
*:before {
-webkit-box-sizing: border-box; -moz-box-sizing: border-box; box-sizing: border-box;
}
* {
-ms-text-size-adjust: 100%; -webkit-text-size-adjust: 100%;
}
html,
body,
.document {
width: 100% !important; height: 100% !important; margin: 0; padding: 0;
}
body {
-webkit-font-smoothing: antialiased; -moz-osx-font-smoothing: grayscale; text-rendering: optimizeLegibility;
}
div[style*="margin: 16px 0"] {
margin: 0 !important;
}
table,
td {
mso-table-lspace: 0pt; mso-table-rspace: 0pt;
}
table {
border-spacing: 0; border-collapse: collapse; table-layout: fixed; margin: 0 auto;
}
img {
-ms-interpolation-mode: bicubic; max-width: 100%; border: 0;
}
*[x-apple-data-detectors] {
color: inherit !important; text-decoration: none !important;
}
.x-gmail-data-detectors,
.x-gmail-data-detectors *,
.aBn {
border-bottom: 0 !important; cursor: default !important;
}
.btn {
-webkit-transition: all 200ms ease; transition: all 200ms ease;
}
.btn:hover {
background-color: #f67575; border-color: #f67575;
}
* {
font-family: Arial, Helvetica, sans-serif; font-size: 18px;
}
@media screen and (max-width: 600px) {
.container {
width: 100%; margin: auto;
}
.stack {
display: block!important; width: 100%!important; max-width: 100%!important;
}
.btn {
display: block; width: 100%; text-align: center;
}
}
body,
p,
td,
tr,
.body,
table,
h1,
h2,
h3,
h4,
h5,
h6,
div,
span {
background-color: #FEFEFE !important; color: #010101 !important;
}
@media (prefers-color-scheme: dark) {
body,
p,
td,
tr,
.body,
table,
h1,
h2,
h3,
h4,
h5,
h6,
div,
span {
background-color: #27292D !important; color: #FEFEFE !important;
}
}
a {
color: inherit !important; text-decoration: underline !important;
}
</style><!--[if mso | ie]>
<style type="text/css">
a {
background-color: #FEFEFE !important; color: #010101 !important;
}
@media (prefers-color-scheme: dark) {
a {
background-color: #27292D !important; color: #FEFEFE !important;
}
}
</style>
<![endif]--></head><body class="">
<div style="display: none; max-height: 0px; overflow: hidden;">Polars’ latest release cycle pushes the streaming engine closer to default use by expanding support to streaming merge joins </div>
<div style="display: none; max-height: 0px; overflow: hidden;">
<br>
</div>
<table align="center" class="document"><tbody><tr><td valign="top">
<table align="center" border="0" cellpadding="0" cellspacing="0" class="container" width="600"><tbody><tr class="inner-body"><td>
<table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr class="header"><td bgcolor="" class="container">
<table width="100%"><tbody><tr><td class="container">
<table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" style="margin-top: 0px;" width="100%"><tbody><tr><td style="padding: 0px;">
<table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding: 15px 15px;">
<div style="text-align: center;">
<span style="margin-right: 0px;"><a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Ftldr.tech%2Fdata%3Futm_source=tldrdata/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/MLf-f9y9vT9Wy02GRM_NabE4PCxxEz4UJHJjKpgeYSg=452" rel="noopener noreferrer" target="_blank"><span>Sign Up</span></a>
|<span style="margin-right: 2px; margin-left: 2px;"><a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fadvertise.tldr.tech%3Futm_source=tldrdata%26utm_medium=newsletter%26utm_campaign=advertisetopnav/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/VT5tA9UPC62P2lVnSuPH_Bxl558rczdwLhO6gEd1i-U=452" rel="noopener noreferrer" target="_blank"><span>Advertise</span></a></span>|<span style="margin-left: 2px;"><a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fa.tldrnewsletter.com%2Fweb-version%3Fep=1%26lc=1670a604-84b7-11f0-bcf5-55fc1d40139c%26p=81f680b0-3c9a-11f1-8ce1-87f28de377b6%26pt=campaign%26t=1776680583%26s=28c493f7e03d907c3f342ad18f18d6f7284fbc202a3a3fdc4c25ba34a309bd6e/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/RNVHpX8jTwXbcg74-5K7nqRj9fI3h0z0vWZmenr3apg=452"><span>View Online</span></a></span>
<br>
</span></div>
</td></tr></tbody></table>
<table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="text-align: center;"><span data-darkreader-inline-color="" style="--darkreader-inline-color:#3db3ff; color: rgb(51, 175, 255) !important; font-size: 30px;">T</span><span style="font-size: 30px;"><span data-darkreader-inline-color="" style="color: rgb(232, 192, 96) !important; --darkreader-inline-color:#e8c163; font-size:30px;">L</span><span data-darkreader-inline-color="" style="color: rgb(101, 195, 173) !important; --darkreader-inline-color:#6ec7b2; font-size:30px;">D</span></span><span data-darkreader-inline-color="" style="--darkreader-inline-color:#dd6e6e; color: rgb(220, 107, 107) !important; font-size: 30px;">R</span>
<br>
</td></tr></tbody></table>
<br>
<table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody></tbody></table>
<table style="table-layout: fixed; width:100%;" width="100%"><tbody><tr><td style="padding:0;border-collapse:collapse;border-spacing:0;margin:0;">
<div style="text-align: center;">
<h1><strong>TLDR Data <span id="date">2026-04-20</span></strong></h1>
</div>
</td></tr></tbody></table>
<table style="table-layout: fixed; width:100%;" width="100%"><tbody></tbody></table>
</td></tr></tbody></table>
</td></tr></tbody></table>
</td></tr>
<tr bgcolor=""><td class="container">
<table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td style="padding: 0px;">
<table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding-top: 0px; padding-bottom: 0px;">
<div class="text-block">
<div style="text-align: center;"><span style="font-size: 36px;">📱</span></div></div>
</td></tr></tbody></table>
<table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding-top: 0px; padding-bottom: 0px;">
<div class="text-block">
<div style="text-align: center;">
<h1><strong>Deep Dives</strong></h1>
</div>
</div>
</td></tr></tbody></table>
<table style="table-layout: fixed; width: 100%;" width="100%"><tbody><tr><td style="padding:0;border-collapse:collapse;border-spacing:0;margin:0;" valign="top">
<table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding: 15px 15px;">
<div class="text-block">
<span>
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fbrunocalza.me%2Fblog%2F2026%2F04%2F13%2Fbuilding-a-grow-only-counter-on-a-sequentially-consistent-kv-store.html%3Futm_source=tldrdata/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/ps9XLCaHD1Rg1YEl1rt6mMwL_TKSZwj2JVCbG5bxyqY=452">
<span>
<strong>Building a Grow-Only Counter on a Sequentially Consistent KV Store (14 minute read)</strong>
</span>
</a>
<br>
<br>
<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
A grow-only counter on a sequentially consistent key-value store can fail because stale reads and concurrent updates may lose increments, even when using compare-and-swap. The article explains CRDT-style counters, consistency models, and why a linearizable store or gossip-based design gives more reliable results.
</span>
</span>
</div>
</td></tr></tbody></table>
<table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding: 15px 15px;">
<div class="text-block">
<span>
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fthenewstack.io%2Fpostgres-iceberg-cdc-benchmarks%2F%3Futm_source=tldrdata/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/QlqoRPcIKoJT0zap5XqdAs87T5NKbpJZiNOADxvmBV0=452">
<span>
<strong>Supermetal vs. Flink vs. Spark for Postgres-to-Iceberg CDC (12 minute read)</strong>
</span>
</a>
<br>
<br>
<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
Postgres-to-Iceberg CDC performance depends heavily on pipeline design, especially during the snapshot phase, not just on connector brand. In this sponsored benchmark, Supermetal's single-node advantage came from a faster CDC path, lower serialization overhead, and phase-aware sink behavior that treats snapshotting and live CDC differently. Flink and Debezium required more tuning and infrastructure. The broader lesson is to benchmark snapshot architecture, tuning knobs, and steady-state CDC separately.
</span>
</span>
</div>
</td></tr></tbody></table>
<table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding: 15px 15px;">
<div class="text-block">
<span>
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fboringsql.com%2Fposts%2Fpostgresql-mvcc-byte-by-byte%2F%3Futm_source=tldrdata/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/_3mMKpEvk4Ca5wGqIusxiCTdRbQ5gq0D6bEJTPFXH7U=452">
<span>
<strong>PostgreSQL MVCC, Byte by Byte (9 minute read)</strong>
</span>
</a>
<br>
<br>
<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
PostgreSQL's MVCC works by storing multiple versions of each row on disk. Every tuple contains xmin and xmax fields that determine its visibility to transactions. Readers never block writers, and writers never block readers. When a row is updated or deleted, a new version is created instead of overwriting the old one. Old versions are cleaned up later by the vacuum process.
</span>
</span>
</div>
</td></tr></tbody></table>
</td></tr></tbody></table>
<table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding-top: 0px; padding-bottom: 0px;">
<div class="text-block">
<div style="text-align: center;"><span style="font-size: 36px;">🚀</span></div>
</div>
</td></tr></tbody></table>
<table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding-top: 0px; padding-bottom: 0px;">
<div class="text-block">
<div style="text-align: center;">
<h1><strong>Opinions & Advice</strong></h1>
</div>
</div>
</td></tr></tbody></table>
<table style="table-layout: fixed; width: 100%;" width="100%"><tbody><tr><td style="padding:0;border-collapse:collapse;border-spacing:0;margin:0;" valign="top">
<table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding: 15px 15px;">
<div class="text-block">
<span>
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Flinks.tldrnewsletter.com%2F23XfR7/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/W3k8ID7QX2bY5Ja9BJu2itYNDRePrNdirToAIanz7L0=452">
<span>
<strong>Daedalus and the Data Labyrinth (5 minute read)</strong>
</span>
</a>
<br>
<br>
<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
The hard part of analytics is often semantic drift, not storage: teams define the same business concept differently, and AI agents make it worse by guessing joins and metrics. Just Eat Takeaway's solution stack is governance as machine-readable context: a business glossary, DataHub catalog with metadata/ownership/lineage/quality, and a semantic layer in Looker where metrics are defined once and reused everywhere. Result: humans and AI query the same trusted definitions.
</span>
</span>
</div>
</td></tr></tbody></table>
<table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding: 15px 15px;">
<div class="text-block">
<span>
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.cio.com%2Farticle%2F4158048%2Fhow-poor-data-foundations-can-undermine-ai-success.html%3Futm_source=tldrdata/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/A2wqUHcpEdxcf83jw136zhs5kErs3sMpj653WXP13f4=452">
<span>
<strong>How poor data foundations can undermine AI success (5 minute read)</strong>
</span>
</a>
<br>
<br>
<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
More than half of generative AI projects were abandoned after POC last year, largely because of poor data readiness. Leaders need to move from curated pilot datasets to production-grade pipelines with consistent definitions, richer metadata, stronger lineage, and automated, real-time governance across structured and unstructured data. Use-case-led prioritization, least-privilege access, auditability, and human-in-the-loop data cleanup can help close the gap.
</span>
</span>
</div>
</td></tr></tbody></table>
<table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding: 15px 15px;">
<div class="text-block">
<span>
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.montecarlodata.com%2Fblog-data-shift-vs-data-drift%3Futm_source=tldrdata/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/XIKiY4g1HXAutRy3UGaVFxdCdqshu6-V2zauPjcPyyI=452">
<span>
<strong>Data Shift vs. Data Drift (6 minute read)</strong>
</span>
</a>
<br>
<br>
<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
Data drift refers to gradual changes in the statistical properties of data (e.g., mean, distribution), while data shift is a sudden, more severe change often caused by upstream system changes, schema updates, or business events. Correctly distinguishing between the two is critical because they require different alerting strategies.
</span>
</span>
</div>
</td></tr></tbody></table>
<table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding: 15px 15px;">
<div class="text-block">
<span>
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Flinks.tldrnewsletter.com%2FBkVfZW/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/AA66qnBwWaoyzyJ8CwVo-BrVtMf1RB8Vatur2hSuNn0=452">
<span>
<strong>Beyond the Demo: Why Agentic Evaluation Matters (9 minute read)</strong>
</span>
</a>
<br>
<br>
<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
Traditional LLM benchmarks are insufficient for evaluating real agentic systems, as they fail to capture long-term reliability, tool usage, planning quality, and recovery from errors in production. Criteo introduced a more rigorous agentic evaluation framework that includes multi-step task completion, error recovery, cost efficiency, and human-aligned success criteria.
</span>
</span>
</div>
</td></tr></tbody></table>
</td></tr></tbody></table>
<table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding-top: 0px; padding-bottom: 0px;">
<div class="text-block">
<div style="text-align: center;"><span style="font-size: 36px;">💻</span></div>
</div>
</td></tr></tbody></table>
<table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding-top: 0px; padding-bottom: 0px;">
<div class="text-block">
<div style="text-align: center;">
<h1><strong>Launches & Tools</strong></h1>
</div>
</div>
</td></tr></tbody></table>
<table style="table-layout: fixed; width: 100%;" width="100%"><tbody><tr><td style="padding:0;border-collapse:collapse;border-spacing:0;margin:0;" valign="top">
<table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding: 15px 15px;">
<div class="text-block">
<span>
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Flinks.tldrnewsletter.com%2F2dApDB%3Futm_source=tldrdata/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/4IJAFGy7A778GXwpQ__CZLh9c25XfdopXQzL9ordlDg=452">
<span>
<strong>Lakebase helps developers get to the real work faster. Skip the waiting and start building (Sponsor)</strong>
</span>
</a>
<br>
<br>
<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
From provisioning databases instantly, to scaling up in a flash and back down to zero, or testing against production data — it's all on the lake. Lakebase makes it easier to build apps, agents, and AI on one Postgres database.<ul><li><a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Flinks.tldrnewsletter.com%2F9Th2er/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/aOlgL8YFeJrWk2DmUwAL6j3AHhy223heQZJBNrqOqeI=452" rel="noopener noreferrer nofollow" target="_blank"><span>Get the Databricks founders' Lakebase rundown</span></a></li>
<li><a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Flinks.tldrnewsletter.com%2Foe5BUY/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/amx8Fd1Ue2i3SoLkwbeDbP4bPRxDq9ktrur2ZytiGa4=452" rel="noopener noreferrer nofollow" target="_blank"><span>Try Lakebase yourself</span></a></li>
</ul>
</span>
</span>
</div>
</td></tr></tbody></table>
<table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding: 15px 15px;">
<div class="text-block">
<span>
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fpola.rs%2Fposts%2Fpolars-in-aggregate-apr26%2F%3Futm_source=tldrdata/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/MyRLBp66H7mlZtces5mKW8Y9XhmljKNr4wmP-XHf_fk=452">
<span>
<strong>Polars in Aggregate: Streaming Expands, Lakehouse I/O, and Cloud Profiling (3 minute read)</strong>
</span>
</a>
<br>
<br>
<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
Polars' latest release cycle pushes the streaming engine closer to default use by expanding support to streaming merge joins, as-of joins, and streaming scans/sinks across CSV, NDJSON, IPC, and cloud reads. It also adds native Delta Lake and Iceberg roundtrips, including direct lazy writes back to Delta and sink_iceberg() for commit-ready streaming pipelines. Polars Cloud now includes query profiling with per-stage CPU, RAM, network, and shuffle metrics.
</span>
</span>
</div>
</td></tr></tbody></table>
<table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding: 15px 15px;">
<div class="text-block">
<span>
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.infoq.com%2Fnews%2F2026%2F04%2Fopentelemetry-declarative-config%2F%3Futm_source=tldrdata/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/ZU5Yzg5EL3nQrUBVTkpWvJELvvjKOmOSRUiuvZz1G2c=452">
<span>
<strong>OpenTelemetry Declarative Configuration Reaches Stability Milestone (3 minute read)</strong>
</span>
</a>
<br>
<br>
<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
OpenTelemetry's declarative configuration spec has reached stability for key parts: the JSON schema, YAML config format, and in-memory model. The vendor-neutral, language-agnostic approach lets teams define traces, metrics, and logs in a single version-controlled YAML file instead of juggling environment variables, SDK init code, and collector configs. Support is available in C++, Go, Java, JavaScript, and PHP, with .NET and Python still in progress.
</span>
</span>
</div>
</td></tr></tbody></table>
<table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding: 15px 15px;">
<div class="text-block">
<span>
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fairflow.apache.org%2Fblog%2Fagentic-workloads-airflow-3%2F%3Futm_source=tldrdata/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/e0OBLyp49PkDxPSOA0U38ga7QaPMg8nVUQXDWPY1cM8=452">
<span>
<strong>Agentic Workloads on Airflow: Observable, Retryable, and Auditable by Design (6 minute read)</strong>
</span>
</a>
<br>
<br>
<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
Airflow 3 introduces first-class support for agentic workflows through features like persistent task state, human-in-the-loop approvals, dynamic task mapping, built-in memory and context management, and tight integration with LLM tooling, allowing teams to orchestrate complex, multi-step agentic applications reliably at scale.
</span>
</span>
</div>
</td></tr></tbody></table>
</td></tr></tbody></table>
<table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding-top: 0px; padding-bottom: 0px;">
<div class="text-block">
<div style="text-align: center;"><span style="font-size: 36px;">🎁</span></div></div>
</td></tr></tbody></table>
<table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding-top: 0px; padding-bottom: 0px;">
<div class="text-block">
<div style="text-align: center;"><strong><h1>Miscellaneous</h1></strong></div>
</div>
</td></tr></tbody></table>
<table bgcolor="" style="table-layout: fixed; width: 100%;" width="100%"><tbody><tr><td style="padding:0;border-collapse:collapse;border-spacing:0;margin:0;" valign="top">
<table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding: 15px 15px;">
<div class="text-block">
<span>
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Flinks.tldrnewsletter.com%2FzXTu6v/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/gMvBRgovKWlSAv9dwHHj7_6BRtuERYG4o8td0g0Hx1E=452">
<span>
<strong>PositionService: Pagination at Scale (16 minute read)</strong>
</span>
</a>
<br>
<br>
<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
Arcesium re-architected their pagination service to handle billions of financial records and ~2 million API calls/day without breaking SLOs. The solution uses cursor-based pagination on date, fetches large indexed chunks (TOP ... WITH TIES), aggregates in SQL, writes the intermediate result to Parquet on S3, and serves later pages with DuckDB from S3. Stable commit timestamps and a uni-temporal model preserve point-in-time consistency across multi-page reads.
</span>
</span>
</div>
</td></tr></tbody></table>
<table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding: 15px 15px;">
<div class="text-block">
<span>
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fengineering.fb.com%2F2026%2F04%2F16%2Fsecurity%2Fpost-quantum-cryptography-migration-at-meta-framework-lessons-and-takeaways%2F%3Futm_source=tldrdata/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/36pFj0sx-9duyR7RjaFF8n2kBTQs1NqudG-JtP9Slyg=452">
<span>
<strong>Post-Quantum Cryptography Migration at Meta: Framework, Lessons, and Takeaways (8 minute read)</strong>
</span>
</a>
<br>
<br>
<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
Quantum computing is expected to break today's public-key cryptography, creating immediate “store now, decrypt later” risk for sensitive data. NIST and the UK NCSC are pushing migration timelines toward 2030, and first standards like ML-KEM (Kyber) and ML-DSA (Dilithium) are now published, with HQC also selected. Meta says it is already rolling out post-quantum encryption internally and recommends a staged approach: crypto inventorying, application risk prioritization, and hybrid deployment to reduce exposure while standards mature.
</span>
</span>
</div>
</td></tr></tbody></table>
</td></tr></tbody></table>
<table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding-top: 0px; padding-bottom: 0px;">
<div class="text-block">
<div style="text-align: center;"><span style="font-size: 36px;">⚡</span></div></div>
</td></tr></tbody></table>
<table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding-top: 0px; padding-bottom: 0px;">
<div class="text-block">
<div style="text-align: center;">
<h1><strong>Quick Links</strong></h1>
</div>
</div>
</td></tr></tbody></table>
<table bgcolor="" style="table-layout: fixed; width: 100%;" width="100%"><tbody><tr><td style="padding:0;border-collapse:collapse;border-spacing:0;margin:0;" valign="top">
<table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding: 15px 15px;">
<div class="text-block">
<span>
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.databricks.com%2Fblog%2Fwhy-frontier-agents-cant-read-documents-and-how-were-fixing-it%3Futm_source=tldrdata/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/7iOFFnk_20AlvogKdN5PIVdA409U0ClnEjMEstf8AEE=452">
<span>
<strong>Why Your Agents Can't Read Enterprise Documents — and How to Fix It (6 minute read)</strong>
</span>
</a>
<br>
<br>
<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
Enterprise agents often fail not because they can't reason, but because they struggle to read messy real-world documents like scans, tables, and handwritten PDFs.
</span>
</span>
</div>
</td></tr></tbody></table>
<table align="center" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding: 15px 15px;">
<div class="text-block">
<span>
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Farize.com%2Fblog%2Fdata-fabric-querying-agent-traces-in-bigquery%2F%3Futm_source=tldrdata/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/5KUP-MmDWjl7E_IVHk-Xaxjkas6Owo1yD2b4WAmMax4=452">
<span>
<strong>Data Fabric: Querying agent traces in BigQuery (6 minute read)</strong>
</span>
</a>
<br>
<br>
<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
Arize Data Fabric writes AI agent traces into open Apache Iceberg tables in Google BigQuery, so teams can analyze AI performance, cost, latency, and business impact with standard SQL.
</span>
</span>
</div>
</td></tr></tbody></table>
</td></tr></tbody></table>
<table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td align="left" style="word-break: break-word; vertical-align: top; padding: 5px 10px;">
<p style="padding: 0; margin: 0; font-size: 22px; color: #000000; line-height: 1.6; font-weight: bold;">
Want to advertise in TLDR? 📰
</p>
<div class="text-block" style="margin-top: 10px;">
If your company is interested in reaching an audience of data engineering professionals and decision makers, you may want to <a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fadvertise.tldr.tech%2F%3Futm_source=tldrdata%26utm_medium=newsletter%26utm_campaign=advertisecta/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/-4EtbbAaD9bjMMbULJXar9R4xanWTFZxk-P574kVlmk=452"><strong><span>advertise with us</span></strong></a>.
</div>
<br>
<!-- New "Want to work at TLDR?" section -->
<p style="padding: 0; margin: 0; font-size: 22px; color: #000000; line-height: 1.6; font-weight: bold;">
Want to work at TLDR? 💼
</p>
<div class="text-block" style="margin-top: 10px;">
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fjobs.ashbyhq.com%2Ftldr.tech/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/fbsfwdDNYCW4IbVIT8flsxRiOghwxxQGnx1ab-ZoGsI=452" rel="noopener noreferrer" style="color: #0000EE; text-decoration: underline;" target="_blank"><strong>Apply here</strong></a>,
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fjobs.ashbyhq.com%2Ftldr.tech%2Fc227b917-a6a4-40ce-8950-d3e165357871/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/Y9nszgVfgqOqYsZo2n0ZImjwZ9vP6UEEs0RMY8W5sr0=452" rel="noopener noreferrer" style="color: #0000EE; text-decoration: underline;" target="_blank"><strong>create your own role</strong></a> or send a friend's resume to <a href="mailto:jobs@tldr.tech" style="color: #0000EE; text-decoration: underline;">jobs@tldr.tech</a> and get $1k if we hire them! TLDR is one of <a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.linkedin.com%2Ffeed%2Fupdate%2Furn:li:activity:7401699691039830016%2F/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/yKvkUSFLWiMzQNptWA0MD53D4Slr4HI6ZRkXjm6DhYI=452" rel="noopener noreferrer" style="color: #0000EE; text-decoration: underline;" target="_blank"><strong>Inc.'s Best Bootstrapped businesses</strong></a> of 2025.
</div>
<br>
<div class="text-block">
If you have any comments or feedback, just respond to this email!
<br>
<br> Thanks for reading,
<br>
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.linkedin.com%2Fin%2Fjoelvanveluwen%2F/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/zRAtZkejffpdqgIsyRjaVzCUQrK2uaNXz6YkQBbSiME=452"><span>Joel Van Veluwen</span></a>, <a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.linkedin.com%2Fin%2Fjennytzurueyching%2F/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/XaHxTssId3MswMG1L-BKjdc7sctE-mdaAh13MVWyPuQ=452"><span>Tzu-Ruey Ching</span></a> & <a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.linkedin.com%2Fin%2Fremi-turpaud%2F/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/ev6KuT-x9nmh0WJn9vfzwH_Bm4DJZ-6tAkFNwfRCInM=452"><span>Remi Turpaud</span></a>
<br>
<br>
</div>
<br>
</td></tr></tbody></table>
<table align="center" bgcolor="" border="0" cellpadding="0" cellspacing="0" width="100%"><tbody><tr><td class="container" style="padding: 15px 15px;">
<div class="text-block" id="testing-id">
<a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Ftldr.tech%2Fdata%2Fmanage%3Femail=silk.theater.56%2540fwdnl.com/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/CNKCRKUYp0mLBuQzOvJgLGJes7_GsMj2iOZmxmHW2Wo=452">Manage your subscriptions</a> to our other newsletters on tech, startups, and programming. Or if TLDR Data isn't for you, please <a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fa.tldrnewsletter.com%2Funsubscribe%3Fep=1%26l=037ede50-92cc-11ee-b0f2-b761aa2217ad%26lc=1670a604-84b7-11f0-bcf5-55fc1d40139c%26p=81f680b0-3c9a-11f1-8ce1-87f28de377b6%26pt=campaign%26pv=4%26spa=1776679233%26t=1776680583%26s=0d2d7206c9c95f90550cf5530888ca893c826bf1ac08efa57cde77e398659b6b/1/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/aq1TsnqYC_9TOeoOq4hivcTx4ebkaI-w_6P6_RRQrYs=452">unsubscribe</a>.
<br>
</div>
</td></tr></tbody></table>
</td></tr></tbody></table>
</td></tr></tbody></table>
</td></tr></tbody></table>
</td></tr></tbody></table>
<img alt="" src="http://tracking.tldrnewsletter.com/CI0/0100019daa6a3f9e-db03b2bd-b11a-4fb6-81c5-ec89fabe62b4-000000/wdkw8y0vO4nD1eSAtzALeo6xvs8mcg4GEggV2E2JC3E=452" style="display: none; width: 1px; height: 1px;">
</body></html>