Access CRM Data with PostgreSQL SQL Queries

In the world of Salesforce, writing SOQL is not just about fetching data — it’s about efficiency, scalability, and performance-driven design. 🔹 Strong Foundation Matters A well-structured SOQL query (SELECT, WHERE, ORDER BY, LIMIT) is the base -but real expertise comes from: ✔ Using relationship queries instead of multiple calls ✔ Avoiding SOQL inside loops ✔ Writing selective queries with indexed fields ✔ Enforcing security using WITH SECURITY_ENFORCED 🔹 Think Beyond Syntax – Think Performance Senior developers don’t just write queries — they optimize systems: ✔ Avoid OFFSET for large datasets (use keyset pagination) ✔ Prevent full table scans with selective filters ✔ Reduce governor limit consumption with smart querying 🔹 Where Real Impact Happens → Aggregate SOQL 💡 This is where junior and senior thinking truly differs. Instead of processing records one-by-one in Apex: 👉 Use Aggregate Queries to let the database do the heavy lifting. ✔ COUNT() → Quickly measure data volume ✔ SUM() / AVG() → Business insights without loops ✔ GROUP BY → Replace complex trigger logic ✔ HAVING → Filter aggregated results efficiently 💥 Real Senior-Level Mindset: “Why loop through 10,000 records in Apex when one aggregate query can solve it in milliseconds?” 🔹 Business Impact ✔ Cleaner trigger logic ✔ Reduced execution time ✔ Better scalability for large data volumes ✔ Optimized automation & reporting 📌 Final Thought Efficient SOQL is not about writing queries - it’s about designing data access strategically. #Salesforce #SOQL #Apex #SalesforceDeveloper #TechLeadership #PerformanceOptimization #CodingBestPractices #SeniorDeveloper

🚨 “Too many query rows: 50001” One of the most common Apex errors in Salesforce! Almost every Salesforce Developer faces this error while working on Triggers, Batch Jobs, Integrations, or Large Data Volume scenarios. But many developers still struggle to fix it properly in production environments. That’s why we created this detailed guide. ⚠️ Quick Check for Salesforce Developers: 1️⃣ What actually causes Too Many Query Rows 50001 error? 2️⃣ Why does it appear even when SOQL looks correct? 3️⃣ How will you handle this in bulk triggers? 4️⃣ Can Batch Apex completely solve this issue? 5️⃣ What is the role of SOQL for loop here? 6️⃣ How will you manage large data volume in production? 7️⃣ What are the best practices to avoid this error permanently? If you are not confident with these, this article is for you. 🔥 New Article Published ✔ What is Too Many Query Rows Error ✔ Why it happens ✔ Real-world Apex scenarios ✔ Production-safe solutions ✔ Best practices and optimization tips 🔗 Read the full article here: https://lnkd.in/gkhUBFTX 💬 Question for Salesforce Developers: 🤝 This is a collaboration article by TriggerHours published on AyanInsights to help Salesforce developers understand and resolve this issue with real-world solutions. --------------------------------------------------------------

❌ “No SOQL in loop” 💥 Still hit Too many SOQL queries: 201 in Production. Yes — this actually happened. Everything looked clean: ✔ Bulkified logic ✔ No queries in loops ✔ Async processing in place Still… it failed. 🔍 Root Cause? The loop was clean. But the execution path wasn’t. 👉 A service method was called inside the loop 👉 That method contained hidden SOQL queries 💣 Result: indirect queries per record → governor limit exceeded 🧠 Biggest Lesson: You don’t just review code. You review the entire execution path. 💡 What I changed: ✔ Moved queries outside loops ✔ Built Map-based data access ✔ Passed data into services (no DB calls inside) ✔ Used Custom Metadata for dynamic logic 🚀 Outcome: ⚡ Zero failures 📈 Faster execution 🧩 Truly scalable design 📌 Final Thought: Hidden SOQL is often more dangerous than visible SOQL. #Salesforce #Apex #GovernorLimits #Bulkification #QueueableApex #BatchApex #SalesforceDeveloper #CRM

Clay keeps choking at 50k rows. So I built its open-source, agent-friendly twin: 🔥 OpenKiln. Here’s the story: Power users know the pain. - Clay gets expensive - The UI slows down - 50k table row limit means you keep hitting walls I got tired of workarounds and credits. So I built OpenKiln by OrbiSearch. OpenKiln is a CLI tool for building data enrichment and outbound pipelines. All open-source. All agent-friendly. Instead of a clunky UI, you control it right from your terminal (or through Telegram, Claude Code, or any coding agent that can run shell commands). The architecture is simple but powerful: - Source: pull data from CRM, CSV, or APIs - Transform: verify emails, enrich contacts, whatever you want - Sink: push results to campaigns or update your CRM Everything runs on a plugin system called "skills." You install only what you need. Each skill owns its own database and commands. Want to build your own integration? Grab the Skill Maker repo. If a service has an API, you can add it. Available out of the box: - CRM (source + sink) - OrbiSearch (transform) - Smartlead (sink) Run a pipeline by chaining skills together in a YAML workflow. Validate before you launch. Scale up without breaking the bank-or your table size. Install in one line: curl -fsSL https://lnkd.in/e2igPnnz | bash Docs, guides, and source code are all public: - Website: https://openkiln.dev - GitHub: https://lnkd.in/eFyQZWR8 - Workflow Guide: https://lnkd.in/ekWHGf-S Tired of platform limits? Try OpenKiln, and let me know what skills or integrations you want to see next. 🔥

🚀 Batch Apex: Iterator vs QueryLocator : When to Use What? While working with Batch Apex, one common confusion is choosing between Iterator and Database.QueryLocator in the start() method. This is also one of the important decisions to keep your batch running smoothly. Here's a simple breakdown : 🔹 1. Database.QueryLocator • Designed for large data volumes (up to 50 million records) • Uses SOQL query directly • Salesforce handles chunking internally using cursor • More efficient for simple, bulk data processing ✅ Best when: 𝗬𝗼𝘂’𝗿𝗲 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 𝘀𝘁𝗮𝗻𝗱𝗮𝗿𝗱 𝗿𝗲𝗰𝗼𝗿𝗱𝘀 𝗳𝗿𝗼𝗺 𝗮 𝘀𝗶𝗻𝗴𝗹𝗲 𝗾𝘂𝗲𝗿𝘆 𝗡𝗼 𝗰𝗼𝗺𝗽𝗹𝗲𝘅 𝗽𝗿𝗲-𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 𝗶𝘀 𝗿𝗲𝗾𝘂𝗶𝗿𝗲𝗱 𝗥𝗲𝗱𝘂𝗰𝗲𝘀 𝘁𝗵𝗲 𝗖𝗣𝗨 𝗮𝗻𝗱 𝗵𝗲𝗮𝗽 𝘂𝘀𝗮𝗴𝗲 𝗧𝗵𝗶𝘀 𝘂𝘁𝗶𝗹𝗶𝘇𝗲𝘀 𝘁𝗵𝗲 𝗯𝗮𝘁𝗰𝗵 𝗮𝗽𝗲𝘅'𝘀 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹𝗶𝘁𝘆 𝘁𝗼 𝗶𝘁𝘀 𝗳𝘂𝗹𝗹𝗲𝘀𝘁 🔹 2. Iterable • Gives full control over the dataset • Can include custom logic, multiple sources, API data • Limited by standard governor limits (no 50M support) ✅ Best when: 𝗗𝗮𝘁𝗮 𝗰𝗼𝗺𝗲𝘀 𝗳𝗿𝗼𝗺 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗼𝗿 𝗰𝗼𝗺𝗽𝗹𝗲𝘅 𝗹𝗼𝗴𝗶𝗰 𝗣𝗿𝗲-𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝗱 𝗯𝗲𝗳𝗼𝗿𝗲 𝗯𝗮𝘁𝗰𝗵 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 💡 On the Whole: 👉 Use QueryLocator for performance & scale 👉 Use Iterable for flexibility & complex logic This is a frequently used concept ,not complex, but clarity matters a lot! #Salesforce #Apex #BatchApex #SalesforceDeveloper #TechLearning

🔁 Dataverse → SQL Integration: What You Need to Know Many organizations try connecting Power Apps or Power Automate directly to SQL, which often leads to data issues, security risks, and maintenance headaches. In my previous post, we explored a secure approach using Custom Connector → API Layer. Today, let’s look at all the options and their pros & cons: Direct SQL Link (Linked Server / Direct Query) ⚡ Pros: Fast access ❌ Cons: Security risks, hard to manage permissions, inflexible Power Automate / Dataflows ✅ Pros: Control, logging, retry ❌ Cons: Slower, depends on flow limits Custom API / Azure Function ✅ Pros: Flexible, secure, scalable ❌ Cons: Needs dev effort Azure Data Factory (ADF) ✅ Pros: Handles large data, schedulable ❌ Cons: Requires Azure setup 💡 Tip: Always balance security, maintainability, and scalability when choosing your integration method. 📢 Question for you: Which integration method have you used in your projects? Share your experience! ⚡ Fact: 70% of integration errors happen due to direct SQL connections without proper business rules. #PowerPlatform #PowerAutomate #PowerApps #SQLServer #CustomConnector #LowCode #DigitalTransformation

Salesforce Random Notes #8: Why Salesforce gives you 50,000 records to query but only 10,000 to update. Ever felt like the SOQL limits were a bit of a "trap"? I was diving deep into data strategy today and hit that classic question: If I can query 50,000 records in one go, why does the system crash the moment I try to update 30,000 of them? Here’s the breakdown for my fellow #Salesforce developers and architects: 1. Read vs. Write Cost: Reading data is "cheap," but writing is "expensive." When you hit "Update," you aren't just changing a cell. You’re triggering a chain reaction of Flows, Triggers, and Validation Rules. The 10k DML limit is there to protect the multi-tenant "engine" from overheating! 2. The "Semi-Join" Surprise: Coming from a SQL background? Watch out! Standard SOQL doesn't support GROUP BY or HAVING inside a subquery. If you need to filter Accounts based on an aggregate count of Contacts, you’ll need to bridge the gap with Apex or a Roll-up Summary field. 3. Scaling for LDV (Large Data Volumes): Moving 100k+ records? ❌ Standard Synchronous Apex will fail. ✅ Batch Apex is your best friend—breaking that 30k update into 150 manageable "chunks" of 200 records. The Golden Rule: • SOQL (50k) is for Analysis. • DML (10k) is for Action. • Batch Apex is for Mass Migration. The platform isn't limiting us; it’s forcing us to build for scale. #SalesforceDeveloper #Apex #SOQL #SalesforceOhana #DataMigration 

Stop wasting time on manual data exports and complex custom coding. In this quick demo, we show how DBSync automates the replication process between Salesforce and SQL Server, keeping your backend and CRM in perfect sync. Why it matters: - Zero Code: Set up your integration in minutes. - Accuracy: Eliminate manual data entry errors. - Efficiency: Focus on insights, not infrastructure. Check out the full demo here: https://lnkd.in/daGhYVf5 #DBSync #Salesforce #SQLServer #DataIntegration #Automation #ProductManagement

A data import without a backup plan is a disaster waiting to happen. Most Salesforce users default to the Data Import Wizard because it's easy. But here's what it can't do: ❌ Back up your data before making changes ❌ Touch key objects like Opportunities or Cases ❌ Give you an undo button if something goes wrong When you're dealing with complex objects or thousands of records, you need the right tool — and that's the Salesforce Data Loader. In our latest tutorial, Jefferson walks through everything you need to get started: 📥 How to download & install Data Loader Step-by-step setup for both Windows and Mac, including how to handle the Mac permissions issue that trips up most first-time users. 💾 How to run a point-in-time backup Before touching anything in your org — especially production — export a full CSV backup of your data. Takes minutes and could save you hours of headache. ✏️ How to run a clean, auditable update Import changes from a CSV, map your fields correctly, and let Data Loader automatically generate a success log and error log for every single record processed. The result? You go from basic Salesforce user to power user — with an audit trail, backup protection, and the ability to handle data operations the wizard simply wasn't built for. 👇 Watch the full setup guide here → https://lnkd.in/gaK42EMK Staring down a large data migration or complex system cleanup? That's exactly what we do at SOLVD. Book a free call with us and let our team handle the heavy lifting. #Salesforce #DataLoader #SalesforceAdmin #DataManagement #SalesforceConsulting #CRMData #DataMigration #SOLVD