🗄️ Storage & Data Lakes
- Amazon S3 – “Data-ah store pannanum-na, S3-la pottu safe-ah vachukonga”
- AWS Lake Formation – “Data lake setup panna AWS-e help panniduvum, neenga tension vendam”
- Amazon S3 Glacier – “Old data-ah cheap-ah store pannum, access slow-ah irukum”
- AWS Storage Gateway – “On-premise and cloud storage-ah connect panniduvum”
🗃️ Databases
- Amazon RDS – “Database manage panna time illa-na, RDS automatic-ah patthukum”
- Amazon DynamoDB – “NoSQL database ku speed venum-na, DynamoDB millisecond-la response kudukum”
- Amazon Aurora – “MySQL/PostgreSQL-ah cloud-native-ah fast-ah panniduvum”
- Amazon DocumentDB – “MongoDB compatible-ah document store panniduvum”
- Amazon Neptune – “Graph database venuma? Relationships-ah Neptune handle panniduvum”
- Amazon Timestream – “Time series data ku specialized database”
- Amazon QLDB – “Ledger database venuma? Immutable records QLDB-la store pannalam”
- Amazon ElastiCache – “Redis/Memcached cache ku ElastiCache use pannalam”
- Amazon MemoryDB – “Redis compatible-ah in-memory database”
📊 Analytics & Business Intelligence
- Amazon Redshift – “Big data analytics ku warehouse venuma? Redshift-la fast-ah query podalam”
- Amazon QuickSight – “Dashboard and visualization ku QuickSight-ah use pannalam”
- Amazon Athena – “S3-la irukura data-ah SQL query pannalam, server vendam”
- Amazon EMR – “Big data processing ku Hadoop/Spark cluster ready panniduvum”
- AWS Glue DataBrew – “Data cleaning visual-ah pannalam, code ezhuda vendam”
🔄 Data Processing & ETL
- AWS Glue – “Data cleaning and transformation ku manual work vendam, Glue serverless-ah panniduvum”
- AWS Data Pipeline – “Data workflow orchestration ku pipeline create pannalam”
- AWS Step Functions – “Complex workflow-ah visual-ah design pannalam”
- Amazon AppFlow – “SaaS applications-la irundhu data sync panniduvum”
⚡ Streaming & Real-time Data
- Amazon Kinesis Data Streams – “Real-time data streaming ku Kinesis use pannalam”
- Amazon Kinesis Data Firehose – “Streaming data-ah automatically S3/Redshift-ku deliver panniduvum”
- Amazon Kinesis Analytics – “Streaming data-ah real-time-la analyze pannalam”
- Amazon MSK – “Managed Kafka service venuma? MSK use pannalam”
🚚 Data Migration & Transfer
- AWS DMS – “Database migration-ku DMS automatic-ah panniduvum”
- AWS DataSync – “On-premise to cloud data sync pannalam”
- AWS Snow Family – “Petabyte data transfer ku physical device use pannalam”
- AWS Transfer Family – “SFTP/FTPS file transfer managed service”
🤖 Machine Learning Data Services
- Amazon SageMaker Data Wrangler – “ML data preparation visual-ah pannalam”
- AWS Data Exchange – “Third-party data marketplace-la data vangalam”
- Amazon Lookout for Metrics – “Anomaly detection automatic-ah panniduvum”
📈 Data Catalog & Governance
- AWS Glue Data Catalog – “Metadata repository-ah centralized-ah maintain pannalam”
- Amazon Macie – “Sensitive data-ah automatically identify and protect panniduvum”
🔍 Search & Analytics
- Amazon OpenSearch – “Elasticsearch cluster managed service-ah use pannalam”
- Amazon CloudSearch – “Simple search service ku CloudSearch use pannalam”
📱 Mobile & IoT Data
- AWS IoT Core – “IoT device data-ah cloud-la collect pannalam”
- AWS IoT Analytics – “IoT data-ah analyze panna specialized service”
- Amazon Timestream – “IoT time series data ku optimized database”
Total: 35+ AWS Data Services!
📸 Instagram: @dataengineeringtamil | 💼 LinkedIn: @sbgowtham
“AWS-la data services neraya iruku, but oru service-ku oru purpose – choose pannitu use pannunga!”
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