Database and Analytics Product Services from Google Azure AWS
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Database Tools/Services
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Sno	Amazon	Azure	Microsoft
1.	Amazon Aurora : High performance managed relational database with full MySQL and PostgreSQL compatibility	SQL : Managed MySQL, PostgreSQL, SQL Server	Azure SQL : Migrate, modernize, and innovate on the modern SQL family of cloud databases
2.	Amazon Aurora Serverless V2 : Instantly scale to >100,000 transactions per second	Datastore : NoSQL database for your web and mobile apps	Azure Cosmos DB : Build or modernize scalable, high-performance apps
3.	Amazon DocumentDB (with MongoDB compatibility) : Fully managed document database	Firestore : Serverless NoSQL document DB	Azure SQL Database : Build apps that scale with managed and intelligent SQL database in the cloud
4.	Amazon DynamoDB : Managed NoSQL database	Spanner : Horizontally scalable relational DB	Azure Database for PostgreSQL : Fully managed, intelligent, and scalable PostgreSQL
5.	Amazon ElastiCache : In-memory caching service	Bigtable : Petabyte-scale, low-latency, non-relational	Azure SQL Managed Instance : Modernize SQL Server applications with a managed, always-up-to-date SQL instance in the cloud
6.	Amazon Keyspaces (for Apache Cassandra) : Managed Cassandra-compatible database	Memorystore : Managed Redis and Memcached	Azure Database for MySQL : Fully managed, scalable MySQL Database
7.	Amazon MemoryDB for Redis : Redis-compatible, durable, in-memory database that delivers ultra-fast performance	Database Migration : Cloud SQL migrations simplified	SQL Server on Azure Virtual Machines : Migrate SQL Server workloads to the cloud at lower total cost of ownership (TCO)
8.	Amazon Neptune : Fully managed graph database service	MongoDB Atlas : JSON-like data models, querying, & scaling	Azure Cache for Redis : Accelerate apps with high-throughput, low-latency data caching
9.	Amazon Quantum Ledger Database (QLDB) : Fully managed ledger database	Neo4j Aura : Integrated, fully managed graph databases	Azure Database Migration Service : Accelerate your data migration to Azure
10.	Amazon RDS : Managed relational database service for MySQL, PostgreSQL, Oracle, SQL Server, and MariaDB	Redis Enterprise : Robust in-memory database platform	Azure Managed Instance for Apache Cassandra : Modernize Cassandra data clusters with a managed instance in the cloud
11.	Amazon RDS on Outposts : Automate on-premises database management	AlloyDB : Enterprise-grade, PostgreSQL-compatible databases	Azure Database for MariaDB : Deploy applications to the cloud with enterprise-ready, fully managed community MariaDB
12.	Amazon Redshift : Fast, simple, cost-effective data warehousing
13.	Amazon Timestream : Fully managed time series database
14.	AWS Database Migration Service : Migrate databases with minimal downtime

Data Analytics Tools/Services
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Sno	Amazon	Azure	Microsoft
1.	Amazon Athena : Query data in S3 using SQL	BigQuery : Data warehouse for business agility and insights.	Azure Synapse Analytics : Limitless analytics with unmatched time to insight
2.	Amazon Cloud : SearchManaged search service	Looker : Platform for BI, data applications, and embedded analytics.	Azure Databricks : Design AI with Apache Spark™-based analytics
3.	Amazon DataZone (Preview) : Unlock data across organizational boundaries with built-in governance	Dataflow : Streaming analytics for stream and batch processing.	Microsoft Purview : Govern, protect, and manage your data estate
4.	Amazon OpenSearch Service : Search, visualize, and analyze up to petabytes of text and unstructured data	Pub/Sub : Messaging service for event ingestion and delivery.	Azure Data Factory : Hybrid data integration at enterprise scale, made easy
5.	Amazon EMR : Easily run big data frameworks	Dataproc : Service for running Apache Spark and Apache Hadoop clusters.	HDInsight : Provision cloud Hadoop, Spark, R Server, HBase, and Storm clusters
6.	Amazon FinSpace : Analytics for the financial services industry	Cloud Data Fusion : Data integration for building and managing data pipelines.	Azure Stream Analytics : Real-time analytics on fast-moving streaming data
7.	Amazon Kinesis : Analyze real-time video and data streams	Cloud Composer : Workflow orchestration service built on Apache Airflow.	Azure Machine Learning : Build, train, and deploy models from the cloud to the edge
8.	Amazon Managed Streaming for Apache Kafka : Fully managed Apache Kafka service	Dataprep : Service to prepare data for analysis and machine learning.	Azure Analysis Services : Enterprise-grade analytics engine as a service
9.	Amazon Redshift : Fast, simple, cost-effective data warehousing	Dataplex : Intelligent data fabric for unifying data management across silos.	Azure Data Lake Storage : Scalable, secure data lake for high-performance analytics
10.	Amazon QuickSight : Fast business analytics service	Looker Studio : Interactive data suite for dashboarding, reporting, and analytics.	Azure Data Explorer : Fast and highly scalable data exploration service
11.	AWS Clean Rooms : Match, analyze, and collaborate on datasets–without sharing or revealing underlying data	Analytics Hub : Service for securely and efficiently exchanging data analytics assets.
12.	AWS Data Exchange : Find, subscribe to, and use third-party data in the cloud
13.	AWS Data Pipeline : Orchestration service for periodic, data-driven workflows
14.	AWS Glue : Simple, scalable, and serverless data integration
15.	AWS Lake Formation : Build, manage, and secure your data lake

Related reading
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Data Lake vs Data Warehouse vs Data Mart vs Lakehouse — concepts behind the lake, warehouse, and lakehouse rows in the tables above
Serverless databases — Aurora Serverless, BigQuery, and similar managed offerings
Selecting Database for Project — how to choose among the options listed here

Author
Dr Hari Thapliyaal
dasarpai.com
linkedin.com/in/harithapliyal

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Dr. Hari Thapliyaal

Writes on data science & AI, project management, and Advaita Vedanta—and builds training and consulting work around those threads.

Education: Doctorate in AI/NLP (SSBM, Geneva); masters study across computer science, business, data science, and economics.
Career: 30+ years in management and technology leadership; 16+ years across the software product lifecycle; a decade in PM training, coaching, and consulting; hands-on Data Science/AI product solution delivery, course design, and mentoring in GenAI, ML, Deep Learning, NLP and Analytics.
Verticals: Solutions and delivery across logistics, BFSI, investment banking, NGOs, staffing, and industrial engineering.
Strengths: Clarifying messy stakeholder problems and turning them into practical outcomes.

Away from work: long meditation and quiet time in nature.