Google Cloud Professional Cloud Database Engineer: key terms

Flashcards for this exam Google Cloud Professional Cloud Database Engineer guide Class dates

• ACIDThe four properties of reliable transactions: Atomicity, Consistency, Isolation and Durability.Foundational
• AlloyDB for PostgreSQLGoogle Cloud fully managed PostgreSQL-compatible database built for high performance transactional and analytical workloads.Advanced
• Apache CassandraAn open-source, masterless, distributed wide-column database designed for high write throughput and multi-datacenter availability.Intermediate
• Asynchronous ReplicationReplication in which the primary acknowledges writes immediately and ships changes to replicas afterward.Intermediate
• B-Tree IndexA balanced tree index that keeps keys sorted and supports equality, range and ORDER BY lookups in logarithmic time.Intermediate
• BigtableGoogle Cloud fully managed wide-column NoSQL database for large-scale, low-latency analytical and operational workloads.Intermediate
• Caching StrategyPatterns for keeping a cache consistent with a database, such as cache-aside (lazy loading), write-through and write-behind.Intermediate
• CAP TheoremThe principle that a distributed data store can guarantee at most two of Consistency, Availability and Partition tolerance during a network partition.Intermediate
• Cloud SQLGoogle Cloud fully managed relational database service for MySQL, PostgreSQL and SQL Server.Foundational
• Composite IndexAn index built on two or more columns, ordered by the first column, then the second, and so on.Intermediate
• Connection PoolingReusing a pool of open database connections across requests instead of opening a new connection each time.Intermediate
• Cypher Query LanguageA declarative graph query language, created by Neo4j, that uses ASCII-art patterns such as (a)-[:REL]->(b) to match nodes and relationships.Advanced
• Database IndexA data structure that speeds up row lookups on one or more columns at the cost of extra storage and slower writes.Foundational
• Database StatisticsMetadata about the distribution of values in columns and indexes, used by the optimizer to estimate row counts.Advanced
• DeadlockA cycle in which two or more transactions each hold a lock the other needs, so none can proceed.Intermediate
• Distributed TransactionA transaction that spans multiple databases or nodes and must still be atomic across all of them.Advanced
• Document DatabaseA NoSQL database that stores self-describing documents (JSON or BSON) whose structure can vary from document to document.Foundational
• Eventual ConsistencyA model in which replicas converge to the same value if no new updates occur, but reads may temporarily return stale data.Intermediate
• FirestoreGoogle Cloud serverless NoSQL document database with real-time synchronization and offline support for web and mobile apps.Intermediate
• Graph DatabaseA database that stores data as nodes and edges with properties, optimized for traversing relationships.Intermediate
• Hash IndexAn index that maps keys through a hash function to buckets, giving very fast equality lookups but no range support.Advanced
• Horizontal PartitioningSplitting a table by rows into several partitions or tables with the same columns.Intermediate
• Hot PartitionA partition or shard that receives a disproportionate share of traffic, creating a bottleneck while others sit idle.Advanced
• In-Memory DatabaseA database that keeps its primary data in RAM for microsecond to millisecond access, often with optional persistence.Intermediate
• Inverted IndexA mapping from each term to the list of documents or rows that contain it, used by search engines and full-text indexes.Intermediate
• Key-Value StoreA NoSQL database that stores data as unique keys mapped to opaque values, optimized for fast lookups by key.Foundational
• Leftmost Prefix RuleThe principle that a composite index can be used for seeks only when queries filter on its leading column(s).Advanced
• MongoDBA popular document database that stores BSON documents in collections and supports rich queries, indexes, aggregation and horizontal sharding.Foundational
• Multiversion Concurrency Control (MVCC)A concurrency method that keeps multiple versions of rows so readers see a consistent snapshot without blocking writers.Advanced
• NoSQL DatabaseA non-relational database that stores data as key-value pairs, documents, wide columns or graphs, usually with a flexible schema.Foundational
• Optimistic Concurrency ControlA strategy that lets transactions proceed without locks and checks for conflicts at write time using version numbers or timestamps.Advanced
• PACELC TheoremAn extension of CAP: if there is a Partition, choose Availability or Consistency; Else, choose Latency or Consistency.Advanced
• Pessimistic Concurrency ControlA strategy that locks data when it is read for update, preventing conflicts by making others wait.Advanced
• Point-in-Time Recovery (PITR)Restoring a database to its exact state at a specific moment, for example just before an accidental delete.Intermediate
• Property GraphA graph model in which nodes and relationships both carry labels and key-value properties.Advanced
• Read CommittedAn isolation level in which a transaction sees only committed data, though values may change between reads.Intermediate
• Read ReplicaAsynchronously replicated, read-only copy of a database used to offload read traffic and support disaster recovery.Intermediate
• RedisAn in-memory key-value data store supporting strings, hashes, lists, sets, sorted sets and streams, widely used for caching.Intermediate
• Relational Database Management System (RDBMS)Software that creates, manages and queries relational databases, enforcing schemas, constraints, security and transactions.Foundational
• SerializableThe strictest isolation level, in which concurrent transactions behave as if they had run one after another.Advanced
• Shard KeyThe field or fields used to decide which shard stores each document or row.Advanced
• ShardingHorizontal partitioning of data across multiple database servers (shards) to scale writes and storage.Intermediate
• Snapshot IsolationAn isolation level in which each transaction reads a consistent snapshot of the data as of its start, using row versions.Advanced
• SpannerGoogle Cloud's fully managed, globally distributed relational database with strong consistency and horizontal scalability.Intermediate
• Strong ConsistencyA guarantee that every read returns the most recent committed write, as if there were a single copy of the data.Intermediate
• Synchronous ReplicationReplication in which a write is acknowledged only after it is committed on both the primary and the replica.Intermediate
• Table PartitioningDividing a large table into smaller physical pieces by a key such as date, while queries still see a single table.Intermediate
• Time-Series Database (TSDB)A database optimized for timestamped measurements, offering fast ingestion, time-based compression, retention and windowed aggregation.Intermediate
• Transaction Isolation LevelA setting that defines which concurrency anomalies a transaction may see: Read Uncommitted, Read Committed, Repeatable Read or Serializable.Intermediate
• Transaction LogA sequential record of every change made by transactions, used for recovery, rollback and replication.Intermediate
• Tunable ConsistencyThe ability to choose, per operation or per account, how many replicas must acknowledge a read or write.Advanced
• Two-Phase Commit (2PC)A protocol that coordinates a distributed transaction: participants first vote to prepare, then all commit or all abort.Advanced
• Wide-Column StoreA NoSQL database that organizes data into rows with dynamic columns grouped into column families, built for massive write throughput.Intermediate
• Write-Ahead Logging (WAL)A technique in which changes are recorded in a durable log before being applied to data files.Advanced