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🥇 @malathi-shetty 11 solved
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PostgreSQL: ACID

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Spark: in memory

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DBMS: rdbms

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Elasticsearch: based on

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Cassandra: wide column

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DataViz: purpose

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DynamoDB: serverless db

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Hadoop: distributed

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MySQL: sql

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Neo4j: graph model

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DataEng: ELT

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Redis: Speed

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PostgreSQL: SQL standard

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Airflow: dag meaning

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MySQL: open source mysql

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MongoDB: BSON

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Limit rows

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DataEng: Batch processing

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MongoDB: _id

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Kafka: broker

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DataEng: Stream processing

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Redis: String type

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Kafka: cluster

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DataEng: Data warehouse

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MongoDB: Schema flexibility

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Pandas: dtypes

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DataEng: Data lake

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Redis: TTL

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PostgreSQL: foreign key

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Pandas: describe

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Null check

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PostgreSQL: data types

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Pandas: info

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MongoDB: updateOne

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DataEng: Format

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MongoDB: deleteMany

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Redis: Increment

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Pandas: select columns

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Left join

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Spark: Lazy trigger

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Cassandra: Database type

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MySQL: Query language

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Neo4j: Query language

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MongoDB: $gt operator

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Join key

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PostgreSQL: join

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MongoDB: sort

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PostgreSQL: left join

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Group by

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DataEng: Data quality

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PostgreSQL: group by

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MongoDB: $set

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DataEng: Ingestion

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DataEng: Apache Spark

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Pandas: rename

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Foreign key

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Index purpose

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DataEng: Spark DataFrame

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PostgreSQL: index

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MongoDB: index purpose

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