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The choice between SQL and NoSQL databases depends on your application's specific needs.

Transactions ensure database operations are reliable using ACID properties.

Database bottlenecks slow down performance, but identifying them helps optimize and scale effectively.

Database per Service ensures each microservice owns its data, reducing dependencies.

B-Trees help databases find data quickly without scanning every row.

Choosing between a shared database and a database per service affects system design significantly.

Sharding splits databases into smaller parts to improve performance and scalability.

Database replication enhances data availability and read performance but has challenges like replication lag.

Choose Elasticsearch for complex text searches, but use databases for structured queries.

Caching helps applications respond faster by serving data from memory instead of hitting the database.

The Cache-Aside Pattern speeds up data retrieval by using a cache to store frequently accessed data.

Cache penetration occurs when requests for non-existent data overload the database.

Scaling databases involves deciding whether to enhance read or write capabilities based on traffic patterns.

Redis is a fast in-memory data store used for caching and low-latency applications.

Read replicas allow databases to handle more read requests by distributing them across multiple copies.

REST API design focuses on creating clean, efficient, and scalable web services.

Connection pooling reuses database connections but can cause issues if misconfigured.

Read-after-write consistency ensures users see their latest updates immediately.

Search engines collect, index, retrieve, and rank documents to provide relevant results.

Cache breakdowns can overwhelm databases, but request coalescing solves this issue.

The Transactional Outbox Pattern ensures database updates and event publishing are synchronized to avoid losing events.

Failover ensures systems remain operational by managing leader changes during failures.

2-Phase Commit helps maintain data consistency in transactions across multiple databases.

Protobuf schema evolution requires careful changes to avoid breaking existing clients.

An inverted index helps search engines quickly find documents containing specific terms.

Elasticsearch uses shards for data distribution and replicas for redundancy.

DNS resolution translates a URL into an IP address for web access.

Availability is about access; reliability is about correct performance.

Functional requirements define what a system does, while non-functional requirements define how it performs.

HLD provides an overview of system architecture, while LLD details implementation specifics.

DNS records like A, CNAME, and MX help route internet traffic and manage services.

Choosing the right distributed lock depends on your system's needs and existing tools.

Cache invalidation is about knowing when to refresh cached data.