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Arpit Bhayani

Temporal Primer - Building Long-Running Systems What Matters in Production RAG Structure of Every LLM Chat How LLMs Really Work Your Monolith Is Already A Distributed System Databases Were Not Designed For This BM25 JOIN Algorithms Venting at Work Comes at a Reputation Cost Why Half Your Skills Expire Every Few Years Multi-Paxos - Consensus in Distributed Databases MySQL Replication Internals Bloom Filters When You Increase Kafka Partitions Product Quantization The Q, K, V Matrices The Day I Accidentally Deleted Production How LLM Inference Works What are Blocking Queues and Why We Need Them Heartbeats in Distributed Systems How Writes Work in Apache Cassandra Redis Replication Internals How to Handle Arrogant Colleagues at Work How Does a CDN Handle Content Replication You Can't Fix Everything on Day One When Emotions Spill Over at Work Why gRPC Uses HTTP2 Meetings With No Agenda Are a Waste of Time Career Longevity Beats Constant Job Hopping Stay Relevant at Higher Salary Levels Why Distributed Systems Need Consensus Algorithms Like Raft Why Do Databases Deadlock and How Do They Resolve It Why and How Cache Locality Can Make Your Code Faster Why Eventual Consistency is Preferred in Distributed Systems Why does DNS use both UDP and TCP Should You Do a Master's My Honest Take Empathy Makes Great Engineers Unstoppable Good Mentors Build People, Not Just Skills Why You Should Always Have Back-Burner Projects Before You Push Back, Know What You're Standing On Be the One They Can Count On How Much Are People Willing to Bet on You How to Get Leadership to Say Yes to Your Project Don't Let Your Best Ideas Die in Silence Be the Person Everyone Wants to Work With The XY Problem and How to Avoid It The Startup Hiring Lie Nobody Talks About You Won't Be Promoted Unless You Ask It's Not Enough to be Right; Learn to be Heard No One Ships Great Software Alone You Don't Win by Proving Others Wrong Appreciate Generously; It Costs Nothing, But Builds Everything Your Soft Skills Aren't Soft at All Before you form an opinion, experience it Why You Need Both Curiosity and Action to Thrive A Daily Worklog Changed Everything How We Handle Mistakes Defines Us Own Your Mistakes Don't Wait. Step Up. Temporary Fixes Are Permanent Why Interviews Are Biased And What Sets You Apart Saying 'This isn't my problem' is actually the problem How to Write Effective OKRs Never Lose a Battle due to Miscommunication When In Doubt, Code It Out How to Follow Up Without Annoying People Lead Projects That Land, Execution Over Everything Abstract Thinking Will Define Your Next Decade We Engineers Suck at Task Estimation Shiny Obect Syndrome in Tech When to Change Jobs - The 3P Framework Comfort and Competition - Know When to Switch Gears Paper Notes - On-demand Container Loading in AWS Lambda Paper Notes - SQL Has Problems. We Can Fix Them Pipe Syntax In SQL Paper Notes - NanoLog - A Nanosecond Scale Logging System Don't Wait, Learn - The Best Resource is Mythical Paper Notes - WTF - The Who to Follow Service at Twitter The Unexpected Benefit of Reading Random Engineering Articles Roadmaps Are Limiting Your Growth Stop Leaving Money on the Table - Negotiate Your Job Offer Never Bad-Mouth Your Past Employers Show You're a Culture Fit Quantify your resume, Know Your Numbers The Importance of Being Likeable in Interviews Questions to Ask Your Interviewer How to Build Trust Through Collaboration Do This, Once You Are Out of the Interview Cycle Stop Pitching Ideas, Start Pitching Projects Read Those Design Docs, Even the Ones That Seem Irrelevant The Best Engineering Lessons Happen During Outages Great Engineers Start Broad LLM Summaries are Ruining Your Learning Turn System Design Interviews into Discussions Title Inflation At Work, Find Your Own Projects 6 Simple Strategies to Cracking Any Tech Interview How to Remain Unblocked Solving the Knapsack Problem with Evolutionary Algorithms Generating Pseudorandom Numbers with LFSR Local vs Global Indexes in Partitioned Databases
Decoding Consistency - The C in ACID
Arpit Bhayani · 2021-07-02 · via Arpit Bhayani

In this short essay, we dive deep and understand the “C” in ACID - Consistency.

In this quick read, we will take a detailed look into Consistency, understand its importance, functioning, and how the database implements it.

What is Consistency?

In the context of databases, Consistency is Correctness, which means that under no circumstance will the data lose its correctness.

Database systems allow us to define rules that the data residing in our database are mandated to adhere to. Few handy rules could be

  • balance of an account should never be negative
  • no orphan mapping: there should not be any mapping of a person whose entry from the database is deleted.
  • no orphan comment: there should not be any comment in the database that does not belong to an existing blog.

These rules can be defined on a database using Constraints, Cascades, and Triggers; for example, Foreign Key constraints, Check constraints, On Delete Cascades, On Update Cascades, etc.

Consistency ACID Database

Role of the database engine in ensuring Consistency

An ACID-compliant database engine has to ensure that the data residing in the database continues to adhere to all the configured rules. Thus, even while executing thousands of concurrent transactions, the database always moves from one consistent state to another.

What happens when the database discovers a violation?

Database Engine rollbacks the changes, which ensures that the database is reverted to a previous consistent state.

What happens when the database does not find any violation?

Database Engine will continue to apply the changes, and once the transaction is marked successful, this state of the database becomes the newer consistent state.

Why is consistency important?

The answer is very relatable. Would you ever want your account to have a negative balance? No. This is thus defined as a rule that the database engine would have to enforce while applying any change to the data.

How does the database ensure Consistency?

Integrity constraints are checked when the changes are being applied to the data.

Cascade operations are performed synchronously along with the transaction. This means that the transaction is not complete until the primary set of queries, along with all the eligible cascades, are applied. Most database engines also provide a way to make them asynchronous, allowing us to keep our transactions leaner.

✨ Next up is “I” in ACID - Isolation. Stay tuned.

References