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

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

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

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

Transactions ensure database operations are reliable using ACID properties.

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

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

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

Distributed caching spreads data across multiple servers for better performance and reliability.

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

Database indexing speeds up data retrieval by allowing quick lookups.

Write-Ahead Log ensures data is safely recorded before changes are made.

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

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

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

Cache eviction policies determine which data to remove when caches are full.

Stateless servers are easier to scale because they don't store user session data locally.

Kafka uses retention to keep historical data and compaction to keep the latest state.

Elasticsearch ILM automates index management to reduce storage costs and meet data needs.

Elasticsearch offers Data Streams for simplicity and Time-Based Indices for control in managing time-series data.

Database isolation levels determine how transactions interact and affect data consistency.

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

FAANG engineers use high-level design principles to create scalable systems.

Consistency models determine what data reads in distributed systems can see.

Consistent hashing helps distribute data across servers with minimal movement.

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

Partition pruning helps databases skip unnecessary data scans, speeding up queries.

Optimistic and pessimistic locking are strategies to manage database access during concurrent transactions.

Kafka uses state stores to remember previous events in stateful stream processing.

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

Cache stampede occurs when many requests hit the database due to a cache miss.

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

The CAP Theorem explains the trade-offs in distributed systems during network failures.

Structured logging helps in quickly identifying issues by organizing log data consistently.

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

API pagination helps manage large datasets by breaking them into smaller parts.

Fail Fast means stopping quickly on errors, while Fail Safe ensures safety in failures.

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

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

Replicas keep your system available, while snapshots allow for data recovery.

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

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

Elasticsearch Data Streams simplify time-series data management with one name for many indices.

Cache invalidation is about knowing when to refresh cached data.

The Bulkhead Pattern isolates resources to protect critical workloads from failures.

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

Availability is about access; reliability is about correct performance.

REST, RPC, and gRPC are different methods for communication in software systems.

A CDN speeds up web applications by caching content closer to users.

Idempotency ensures that repeated operations in APIs do not cause duplicate effects.

Elasticsearch uses distributed architecture to search data quickly across multiple servers.

Database replication helps keep data available and allows systems to handle more read requests.

Choosing the right boundaries for microservices is crucial for effective architecture.